Audio Encoder for Encoding an Audio Signal, Method for Encoding an Audio Signal and Computer Program under Consideration of a Detected Peak Spectral Region in an Upper Frequency Band Specification The present invention relates to audio encoding and, preferably, to a method, apparatus or computer program for controlling the quantization of spectral coefficients for the MDCT based TCX in the EVS codec. A reference document for the EVS codec is 3GPP TS 24.445 V13.1.0 (2016-03), 3rd generation partnership project; Technical Specification Group Services and System Aspects; Codec for Enhanced Voice Services (EVS); Detailed algorithmic description (release 13). However, the present invention is additionally useful in other EVS versions as, for example, defined by other releases than release 13 and, additionally, the present invention is additionally useful in all other audio encoders different from EVS that, however, rely on a detector, a shaper and a quantizer and coder stage as defined, for example, in the claims. Additionally, it is to be noted that all embodiments defined not only by the independent but also defined by the dependent claims can be used separately from each other or together as outlined by the interdependencies of the claims or as discussed later on under pre-f erred examples. The EVS Codec [1 ], as specified in 3GPP, is a modern hybrid-codec for narrow-band NB), wide-band (WB), super-wide-band (SWB) or full-band (FB) speech and audio content, which can switch between several coding approaches, based on signal classification: Fig. 1 illustrates a common processing and different coding schemes in EVS. Particularly, a common processing portion of the encoder in Fig. 1 comprises a signal resampling block 101 , and a signal analysis block 102. The audio input signal is input at an audio signal input 103 into the common processing portion and, particularly, into the signal resampling block 101 . The signal resampling block 101 additionally has a command line input for receiving command line parameters. The output of the common processing stage is input in different elements as can be seen in Fig. 1. Particularly, Fig. 1 comprises a linear prediction-based coding block (LP-based coding) 1 10, a frequency domain coding block 120 and an inactive signal coding/CNG block 130. Blocks 1 10, 120, 130 are connected to a bitstream multiplexer 140. Additionally, a switch 150 is provided for switching, depending on a classifier decision, the output of the common processing stage to either the LP-based coding block 1 10, the frequency domain coding block 120 or the inactive signal coding/CNG (comfort noise generation) block 130. Furthermore, the bitstream multiplexer 140 receives a classifier information, i.e., whether a certain current portion of the input signal input at block 103 and processed by the common processing portion is en-coded using any of the blocks 1 10, 120, 130. - The LP-based (linear prediction based) coding, such as CELP coding, is primarily used for speech or speech-dominant content and generic audio content with high temporal fluctuation. The Frequency Domain Coding is used for all other generic audio content, such as music or background noise. To provide maximum quality for low and medium bitrates, frequent switching between LP-based Coding and Frequency Domain Coding is performed, based on Signal Analysis in a Common Processing Module. To save on complexity, the codec was optimized to re-use elements of the signal analysis stage also in subsequent modules. For example: The Signal Analysis module features an LP analysis stage. The resulting LP-filter coefficients (LPC) and residual signal are firstly used for several signal analysis steps, such as the Voice Activity Detector (VAD) or speech/music classifier. Secondly, the LPC is also an elementary part of the LP-based Coding scheme and the Frequency Domain Coding scheme. To save on complexity, the LP analysis is performed at the internal sampling rate of the CELP coder (SRCELP). The CELP coder operates at either 12.8 or 16 kHz internal sampling-rate (SRCELP). and can thus represent signals up to 6.4 or 8 kHz audio bandwidth directly. For audio content exceeding this bandwidth at WB, SWB or FB, the audio content above CELP's frequency representation is coded by a bandwidth-extension mechanism. The MDCT-based TCX is a submode of the Frequency Domain Coding. Like for the LP-based coding approach, noise-shaping in TCX is performed based on an LP-filter. This LPC shaping is performed in the MDCT domain by applying gain factors computed from weighted quantized LP filter coefficients to the MDCT spectrum (decoder-side). On encoder-side, the inverse gain factors are applied before the rate loop. This is subsequently referred to as application of LPC shaping gains. The TCX operates on the input sampling rate (SRinp). This is exploited to code the full spectrum directly in the MDCT domain, without additional bandwidth extension. The input sampling rate SRinp, on which the MDCT transform is performed, can be higher than the CELP sampling rate SRCELP, for which LP coefficients are computed. Thus LPC shaping gains can only be computed for the part of the MDCT spectrum corresponding to the CELP frequency range (fcELp)- For the remain-ing part of the spectrum (if any) the shaping gain of the highest frequency band is used. Fig. 2 illustrates on a high level the application of LPC shaping gains and for the MDCT based TCX. . Particularly, Fig. 2 illustrates a principle of noise-shaping and coding in the TCX or frequency domain coding block 120 of Fig. 1 on the encoder-side. Particularly, Fig. 2 illustrates a schematic block diagram of an encoder. The input signal 103 is input into the resampling block 201 in order to perform a resampling of the signal to the CELP sampling rate SRCELP, i.e., the sampling rate required by LP-based coding block 1 10 of Fig. 1. Furthermore, an LPC calculator 203 is provided that calculates LPC parameters and in block 205, an LPC-based weighting is performed in order to have the signal further processed by the LP-based coding block 1 10 in Fig. 1 , i.e., the LPC residual signal that is encoded using the ACELP processor. Additionally, the input signal 103 is input, without any resampling, to a time-spectral converter 207 that is exempiarily illustrated as an MDCT transform. Furthermore, in block 209, the LPC parameters calculated by block 203 are applied after some calculations. Particularly, block 209 receives the LPC parameters calculated from block 203 via line 213 or alternatively or additionally from block 205 and then derives the MDCT or, generally, spectral domain weighting factors in order to apply the corresponding inverse LPC shaping gains. Then, in block 21 1 , a general quantizer/encoder operation is performed that can, for example, be a rate loop that adjusts the global gain and, additionally, per-forms a quantization/coding of spectral coefficients, preferably using arithmetic coding as illustrated in the well-known EVS encoder specification to finally obtain the bitstream. In contrast to the CELP coding approach, which combines a core-coder at SRCELP and a bandwidth-extension mechanism running at a higher sampling rate, the MDCT-based coding approaches directly operate on the input sampling rate SRINP and code the content of the full spectrum in the MDCT domain. The MDCT-based TCX codes up to 16 kHz audio content at low bitrates, such as 9.6 or 13.2 kbit/s SWB. Since at such low bitrates only a small subset of the spectral coefficients can be coded directly by means of the arithmetic coder, the resulting gaps (regions of zero values) in the spectrum are concealed by two mechanisms: Noise Filling, which inserts random noise in the decoded spectrum. The energy of the noise is controlled by a gain factor, which transmitted in the bitstream. Intelligent Gap Filling (IGF), which inserts signal portions from lower frequencies parts of the spectrum. The characteristics of these inserted frequency-portions are controlled by parameters, which are transmitted in the bitstream. The Noise Filling is used for lower frequency portions up to the highest frequency, which can be controlled by the transmitted LPC (fCEip)- Above this frequency, the IGF tool is used, which provides other mechanisms to control the level of the inserted frequency por-tions. There are two mechanisms for the decision on which spectral coefficients survive the coding procedure, or which will be replaced by noise filling or IGF: Rate loop After the application of inverse LPC shaping gains, a rate loop is applied. For this, a global gain is estimated. Subsequently, the spectral coefficients are quantized, and the quantized spectral coefficients are coded with the arithmetic coder. Based on the real or an estimated bit-demand of the arithmetic coder and the quantization error, the global gain is increased or decreased. This impacts the precision of the quantizer. The lower the precision, the more spectral coefficients are quantized to zero. Applying the inverse LPC shaping gains using a weighted LPC before the rate loop assures that the perceptually relevant lines survive by a significantly higher probability than perceptually irrelevant content. 2) IGF Tonal mask Above fcELP, where the no LPC is available, a different mechanism to identify the perceptually relevant spectral components is used: Line-wise energy is compared to the average energy in the IGF region. Predominant spectral lines, which corre- spond to perceptually relevant signal portions, are kept, all other lines are set to zero. The MDCT spectrum, which was preprocessed with the IGF Tonal mask is subsequently fed into the Rate loop. The weighted LPC follows the spectral envelope of the signal. By applying the inverse LPC shaping gains using the weighted LPC a perceptual whitening of the spectrum is performed. This significantly reduces the dynamics of the MDCT spectrum before the coding-loop, and thus also controls the bit-distribution among the MDCT spectral coefficients in the coding-loop. As explained above, the weighted LPC is not available for frequencies above fcEi_p- For these MDCT coefficients, the shaping gain of the highest frequency band below fCELP is applied. This works well in cases where the shaping gain of the highest frequency band below fcELP roughly corresponds to the energy of the coefficients above fCELP. which is of-ten the case due to the spectral tilt, and which can be observed in most audio signals. Hence, this procedure is advantageous, since the shaping information for the upper band need not be calculated or transmitted. However, in case there are strong spectral components above fcEip and the shaping gain of the highest frequency band below fcELP is very low, this results in a mismatch. This mismatch heavily impacts the work or the rate loop, which focuses on the spectral coefficients having the highest amplitude. This will at low bitrates zero out the remaining signal components, especially in the low-band, and produces perceptually bad quality. Figures 3-6 illustrate the problem. Figure 3 shows the absolute MDCT spectrum before the application of the inverse LPC shaping gains, Figure 4 the corresponding LPC shaping gains. There are strong peaks above fCEi visible, which are in the same order of magnitude as the highest peaks below ½ι.ρ· The spectral components above fCEi_p are a result of the preprocessing using the IGF tonal mask. Figure 5 shows the absolute MDCT spec-trum after applying the inverse LPC gains, still before quantization. Now the peaks above fcELP significantly exceed the peaks below fCFi p, with the effect that the rate-loop will primarily focus on these peaks. Figure 6 shows the result of the rate loop at low bitrates: All spectral components except the peaks above fCtip were quantized to 0. This results in a perceptually very poor result after the complete decoding process, since the psychoa-coustically very relevant signal portions at low frequencies are missing completely. Fig. 3 illustrates an MDCT spectrum of a critical frame before the application of inverse LPC shaping gains. Fig. 4 illustrates LPC shaping gains as applied. On the encoder-side, the spectrum is multiplied with the inverse gain. The last gain value is used for all MDCT coefficients above fCELP- Fig. 4 indicates fcELP at the right border. Fig. 5 illustrates an MDCT spectrum of a critical frame after application of inverse LPC shaping gains. The high peaks above fCE_p are clearly visible. Fig. 6 illustrates an MDCT spectrum of a critical frame after quantization. The displayed spectrum includes the application of the global gain, but without the LPC shaping gains. It can be seen that all spectral coefficients except the peak above fCEi_p are quantized to 0. It is an object of the present invention to provide an improved audio encoding concept. This object is achieved by an audio encoder of claim 1 , a method for encoding an audio signal of claim 25 or a computer program of claim 26. The present invention is based on the finding that such prior art problems can be addressed by preprocessing the audio signal to be encoded depending on a specific characteristic of the quantizer and coder stage included in the audio encoder. To this end, a peak spectral region in an upper frequency band of the audio signal is detected. Then, a shaper for shaping the lower frequency band using shaping information for the lower band and for shaping the upper frequency band using at least a portion of the shaping information for the lower band is used. Particularly, the shaper is additionally configured to attenuate spectral values in a detected peak spectral region, i.e., in a peak spectral region detected by the detector in the upper frequency band of the audio signal. Then, the shaped lower frequency band and the attenuated upper frequency band are quantized and entropy-encoded. Due to the fact that the upper frequency band has been attenuated selectively, i.e., within the detected peak spectral region, this detected peak spectral region cannot fully dominate the behavior of the quantizer and coder stage anymore. Instead, due to the fact that an attenuation has been formed in the upper frequency band of the audio signal, the overall perceptual quality of the result of the encoding operation is improved. Particularly at low bitrates, where a quite low bitrate is a main target of the quantizer and coder stage, high spectral peaks in the upper frequency band would con-sume all the bits required by the quantizer and coder stage, since the coder would be guided by the high upper frequency portions and would, therefore, use most of the available bits in these portions. This automatically results in a situation where any bits for perceptually more important lower frequency ranges are not available anymore. Thus, such a procedure would result in a signal only having encoded high frequency portions while the lower frequency portions are not coded at all or are only encoded very coarsely. However, it has been found that such a procedure is less perceptually pleasant compared to a situation, where such a problematic situation with predominant high spectral regions is detected and the peaks in the higher frequency range are attenuated before performing the encoder procedure comprising a quantizer and a entropy encoder stage. Preferably, the peak spectral region is detected in the upper frequency band of an DCT spectrai. However, other time-spectral converters can be used as well such as a fil-terbank, a QMF filter bank, a DFT, an FFT or any other time-frequency conversion. Furthermore, the present invention is useful in that, for the upper frequency band, it is not required to calculate shaping information. Instead, a shaping information originally calculated for the lower frequency band is used for shaping the upper frequency band. Thus, the present invention provides a computationally very efficient encoder since a low band shaping information can also be used for shaping the high band, since problems that might result from such a situation, i.e., high spectral values in the upper frequency band are addressed by the additional attenuation additionally applied by the shaper in addition to the straightforward shaping typically based on the spectral envelope of the low band signal that can, for example, be characterized by a LPC parameters for the low band signal. But the spectral envelope can also be represented by any other corresponding meas-ure that is usable for performing a shaping in the spectral domain. The quantizer and coder stage performs a quantizing and coding operation on the shaped signal, i.e., on the shaped low band signal and on the shaped high band signal, but the shaped high band signal additionally has received the additional attenuation. Although the attenuation of the high band in the detected peak spectral region is a preprocessing operation that cannot be recovered by the decoder anymore, the result of the decoder is nevertheless more pleasant compared to a situation, where the additional attenuation is not applied, since the attenuation results in the fact that bits are remaining for the perceptually more important lower frequency band. Thus, in problematic situations where a high spectral region with peaks would dominate the whole coding result, the present invention provides for an additional attenuation of such peaks so that, in the end, the encoder "sees" a signal having attenuated high frequency portions and, therefore, the encoded signal still has useful and perceptually pleasant low frequency information. The "sacrifice" with respect to the high spectral band is not or almost not noticeable by listeners, since listeners, generally, do not have a clear picture of the high frequency content of a signal but have, to a much higher probability, an expectation regarding the low frequency content. In other words, a signal that has very low level low frequency content but a significant high level frequency content is a signal that is typically perceived to be unnatu-ral. Preferred embodiments of the invention comprise a linear prediction analyzer for deriving linear prediction coefficients for a time frame and these linear prediction coefficients represent the shaping information or the shaping information is derived from those linear pre-diction coefficients. In a further embodiment, several shaping factors are calculated for several subbands of the lower frequency band, and for the weighting in the higher frequency band, the shaping factor calculated for the highest subband of the low frequency band is used. In a further embodiment, the detector determines a peak spectral region in the upper frequency band when at least one of a group of conditions is true, where the group of conditions comprises at least a low frequency band amplitude condition, a peak distance condition and a peak amplitude condition. Even more preferably, a peak spectral region is only detected when two conditions are true at the same time and even more preferably, a peak spectral region is only detected when all three conditions are true. In a further embodiment, the detector determines several values used for examining the conditions either before or after the shaping operation with or without the additional atten-uation. In an embodiment, the shaper additionally attenuates the spectral values using an attenuation factor, where this attenuation factor is derived from a maximum spectral amplitude in the lower frequency band multiplied by a predetermined number being greater than or equal to 1 and divided by the maximum spectral amplitude in the upper frequency band. Furthermore, the specific way, as to how the additional attenuation is applied, can be done in several different ways. One way is that the shaper firstly performs the weighting information using at least a portion of the shaping information for the lower frequency band in order to shape the spectral values in the detected peak spectral region. Then, a subsequent weighting operation is performed using the attenuation information. An alternative procedure is to firstly apply a weighting operation using the attenuation information and to then perform a subsequent weighting using a weighting information corresponding to the at least the portion of the shaping information for the lower frequency band. A further alternative is to apply a single weighting information using a combined weighting information that is derived from the attenuation on the one hand and the portion of the shaping information for the lower frequency band on the other hand. In a situation where the weighting is performed using a multiplication, the attenuation in-formation is an attenuation factor and the shaping information is a shaping factor and the actual combined weighting information is a weighting factor, i.e., a single weighting factor for the single weighting information, where this single weighting factor is derived by multiplying the attenuation information and the shaping information for the lower band. Thus, it becomes clear that the shaper can be implemented in many different ways, but, neverthe-less, the result is a shaping of the high frequency band using shaping information of the lower band and an additional attenuation. In an embodiment, the quantizer and coder stage comprises a rate loop processor for estimating a quantizer characteristic so that the predetermined bitrate of an entropy en-coded audio signal is obtained. In an embodiment, this quantizer characteristic is a global gain, i.e., a gain value applied to the whole frequency range, i.e., applied to all the spectral values that are to be quantized and encoded. When it appears that the required bitrate is lower than a bitrate obtained using a certain global gain, then the global gain is increased and it is determined whether the actual bitrate is now in line with the requirement, i.e., is now smaller than or equal to the required bitrate. This procedure is performed, when the global gain is used in the encoder before the quantization in such a way the spectral val- ues are divided by the global gain. When, however, the global gain is used differently, i.e., by multiplying the spectral values by the global gain before performing the quantization, then the global gain is decreased when an actual bitrate is too high, or the global gain can be increased when the actual bitrate is lower than admissible. However, other encoder stage characteristics can be used as well in a certain rate loop condition. One way would, for example, be a frequency-selective gain. A further procedure would be to adjust the band width of the audio signal depending on the required bitrate. Generally, different quantizer characteristics can be influenced so that, in the end, a bit rate is obtained that is in line with the required (typically iow) bitrate. Preferably, this procedure is particularly well suited for being combined with intelligent gap filling processing (IGF processing). In this procedure, a tonal mask processor is applied for determining, in the upper frequency band, a first group of spectral values to be quan-tized and entropy encoded and a second group of spectral values to be parametrically encoded by the gap-filling procedure. The tonal mask processor sets the second group of spectral values to 0 values so that these values do not consume many bits in the quantizer/encoder stage. On the other hand, it appears that typically values belonging to the first group of spectral values that are to be quantized and entropy coded are the values in the peak spectral region that, under certain circumstances, can be detected and additionally attenuated in case of a problematic situation for the quantizer/encoder stage. Therefore, the combination of a tonal mask processor within an intelligent gap-filling framework with the additional attenuation of detected peak spectral regions results in a very efficient encoder procedure which is, additionally, backward-compatible and, nevertheless, results in a good perceptual quality even at very low bitrates. Embodiments are advantageous over potential solutions to deal with this problem that include methods to extend the frequency range of the LPC or other means to better fit the gains applied to frequencies above fCELP to the actual MDCT spectral coefficients. This procedure, however, destroys backward compatibility, when a codec is already deployed in the market, and the previously described methods would break interoperability to existing implementations. Subsequently, preferred embodiments of the present invention are illustrated with respect to the accompanying drawings, in which: Fig. 1 illustrates a common processing and different coding schemes in EVS; Fig. 2 illustrates a principle of noise-shaping and coding in the TCX on the encoder- side; Fig. 3 illustrates an MDCT spectrum of a critical frame before the application of inverse LPC shaping gains; Fig. 4 illustrates the situation of Fig. 3, but with the LPC shaping gains applied; Fig. 5 illustrates an MDCT spectrum of a critical frame after the application of inverse LPC shaping gains, where the high peaks above fcELP are clearly visible; Fig. 6 illustrates an MDCT spectrum of a critical frame after quantization only having high pass information and not having any low pass information; Fig. 7 illustrates an MDCT spectrum of a critical frame after the application of inverse LPC shaping gains and the inventive encoder-side pre-processing; Fig. 8 illustrates a preferred embodiment of an audio encoder for encoding an audio signal; Fig. 9 illustrates the situation for the calculation of different shaping information for different frequency bands and the usage of the lower band shaping information for the higher band; Fig, 10 illustrates a preferred embodiment of an audio encoder; Fig. 1 1 illustrates a flow chart for illustrating the functionality of the detector for detecting the peak spectral region; Fig. 12 illustrates a preferred implementation of the implementation of the low band amplitude condition; Fig. 13 illustrates a preferred embodiment of the implementation of the peak distance condition; Fig. 14 illustrates a preferred implementation of the implementation of the peak amplitude condition; Fig. 15a illustrates a preferred implementation of the quantizer and coder stage; Fig. 15b illustrates a flow chart for illustrating the operation of the quantizer and coder stage as a rate loop processor; Fig. 16 illustrates a determination procedure for determining the attenuation factor in a preferred embodiment; and Fig. 17 illustrates a preferred implementation for applying the low band shaping information to the upper frequency band and the additional attenuation of the shaped spectral values in two subsequent steps. Fig. 8 illustrates a preferred embodiment of an audio encoder for encoding an audio signal 403 having a lower frequency band and an upper frequency band. The audio encoder comprises a detector 802 for detecting a peak spectral region in the upper frequency band of the audio signal 103. Furthermore, the audio encoder comprises a shaper 804 for shaping the lower frequency band using shaping information for the lower band and for shaping the upper frequency band using at least a portion of the shaping information for the lower frequency band. Additionally, the shaper is configured to additionally attenuate spectral values in the detected peak spectral region in the upper frequency band. Thus, the shaper 804 performs a kind of "single shaping" in the low-band using the shaping information for the low-band. Furthermore, the shaper additionally performs a kind of a "single" shaping in the high-band using the shaping information for the low-band and typically, the highest frequency low-band. This "single" shaping is performed in some embod-iments in the high-band where no peak spectral region has been detected by the detector 802. Furthermore, for the peak spectral region within the high-band, a kind of a "double" shaping is performed, i.e., the shaping information from the low-band is applied to the peak spectral region and, additionally, the additional attenuation is applied to the peak spectral region. The result of the shaper 804 is a shaped signal 805. The shaped signal is a shaped lower frequency band and a shaped upper frequency band, where the shaped upper frequency band comprises the peak spectral region. This shaped signal 805 is forwarded to a quantizer and coder stage 806 for quantizing the shaped lower frequency band and the shaped upper frequency band including the peak spectral region and for entropy coding the quantized spectral values from the shaped lower frequency band and the shaped upper frequency band comprising the peak spectral region again to obtain the encoded audio signal 814. Preferably, the audio encoder comprises a linear prediction coding analyzer 808 for deriving linear prediction coefficients for a time frame of the audio signal by analyzing a block of audio samples in the time frame. Preferably, these audio samples are band-iimited to the lower frequency band. Additionally, the shaper 804 is configured to shape the lower frequency band using the linear prediction coefficients as the shaping information as illustrated at 812 in Fig. 8. Additionally, the shaper 804 is configured to use at least the portion of the linear prediction coefficients derived from the block of audio samples band-limited to the lower frequency band for shaping the upper frequency band in the time frame of the audio signal. As illustrated in Fig. 9, the lower frequency band is preferably subdivided into a plurality of subbands such as, exemplarily four subbands SB1 , SB2, SB3 and SB4. Additionally, as schematically illustrated, the subband width increases from lower to higher subbands, i.e., the subband SB4 is broader in frequency than the subband SB1. In other embodiments, however, bands having an equal bandwidth can be used as well. The subbands SB1 to SB4 extend up to the border frequency which is, for example, fcEL -Thus, all the subbands below the border frequency fCEi.p constitute the lower band and the frequency content above the border frequency constitutes the higher band. Particularly, the LPC analyzer 808 of Fig. 8 typically calculates shaping information for each subband individually. Thus, the LPC analyzer 808 preferably calculates four different kinds of subband information for the four subbands SB1 to SB4 so that each subband has its associated shaping information. Furthermore, the shaping is applied by the shaper 804 for each subband SB1 to SB4 using the shaping information calculated for exactly this subband and, importantly, a shaping for the higher band is also done, but the shaping information for the higher band is not being calculated due to the fact that the linear prediction analyzer calculating the shaping information receives a band limited signal band limited to the lower frequency band. Nevertheless, in order to also perform a shaping for the higher frequency band, the shaping information for subband SB4 is used for shaping the higher band. Thus, the shaper 804 is configured to weigh the spectral coefficients of the upper frequency band using a shaping factor calculated for a highest subband of the lower frequency band. The highest subband corresponding to SB4 in Fig. 9 has a highest center frequency among all center frequencies of subbands of the lower frequency band. Fig. 1 1 illustrates a preferred flowchart for explaining the functionality of the detector 802. Particularly, the detector 802 is configured to determine a peak spectral region in the up-per frequency band, when at least one of a group of conditions is true, where the group of conditions comprises a low-band amplitude condition 1 102, a peak distance condition 1 104 and a peak amplitude condition 1 106. Preferably, the different conditions are applied in exactly the order illustrated in Fig. 1 1. In other words, the low-band amplitude condition 1 102 is calculated before the peak distance condition 1 104, and the peak distance condition is calculated before the peak amplitude condition 1 106. In a situation, where all three conditions must be true in order to detect the peak spectral region, a computationally efficient detector is obtained by applying the sequential processing in Fig. 1 1 , where, as soon as a certain condition is not true, i.e., is false, the detection process for a certain time frame is stopped and it is determined that an attenuation of a peak spectral region in this time frame is not required. Thus, when it is already determined for a certain time frame that the low-band amplitude condition 1 102 is not fulfilled, i.e., is false, then the control proceeds to the decision that an attenuation of a peak spectral region in this time frame is not necessary and the procedure goes on with-out any additional attenuation. When, however, the controller determines for condition 1 102 that same is true, the second condition 1 104 is determined. This peak distance condition is once again determined before the peak amplitude 1 106 so that the control determines that no attenuation of the peak spectral region is performed, when condition 1 104 results in a false result. Only when the peak distance condition 1 104 has a true result, the third peak amplitude condition 1 106 is determined. In other embodiments, more or less conditions can be determined, and a sequential or parallel determination can be performed, although the sequential determination as exem-plarily illustrated in Fig. 1 1 is preferred in order to save computational resources that are particularly valuable in mobile applications that are battery powered. Figs. 12, 13, 14 provide preferred embodiments for the conditions 1 102, 1104 and 1 106. In the low-band amplitude condition, a maximum spectral amplitude in the lower band is determined as illustrated at block 1202. This value is maxjow. Furthermore, in block 1204, a maximum spectral amplitude in the upper band is determined that is indicated as max_high. In block 1206, the determined values from blocks 1232 and 1234 are processed preferably together with a predetermined number Ci in order to obtain the false or true result of condition 1 102. Preferably, the conditions in blocks 1202 and 1204 are performed before shaping with the lower band shaping information, i.e., before the procedure performed by the spectral shaper 804 or, with respect to Fig. 10, 804a. With respect to the predetermined number C| of Fig. 12 used in block 1206, a value of 16 is preferred, but values between 4 and 30 have been proven useful as well. Fig. 13 illustrates a preferred embodiment of the peak distance condition. In block 1302, a first maximum spectral amplitude in the lower band is determined that is indicated as max low. Furthermore, a first spectral distance is determined as illustrated at block 1304. This first spectral distance is indicated as distjow. Particularly, the first spectral distance is a distance of the first maximum spectral amplitude as determined by block 1302 from a border frequency between a center frequency of the lower frequency band and a center frequency of the upper frequency band. Preferably, the border frequency is f_celp, but this fre-quency can have any other value as outlined before. Furthermore, block 1306 determines a second maximum spectral amplitude in the upper band that is called max_high. Furthermore, a second spectral distance 308 is determined and indicated as dist_high. The second spectral distance of the second maximum spectral amplitude from the border frequency is once again preferably determined with spectral f_celp as the border frequency. Furthermore, in block 1310, it is determined whether the peak distance condition is true, when the first maximum spectra! amplitude weighted by the first spectral distance and weighted by a predetermined number being greater than 1 is greater than the second maximum spectral amplitude weighted by the second spectral distance. Preferably, a predetermined number c2 is equal to 4 in the most preferred embodiment. Values between 1 .5 and 8 have been proven as useful. Preferably, the determination in block 1302 and 1306 is performed after shaping with the lower band shaping information, i.e., subsequent to block 804a, but, of course, before block 804b in Fig. 10. Fig. 14 illustrates a preferred implementation of the peak amplitude condition. Particularly, block 1402 determines a first maximum spectral amplitude in the lower band and block 1404 determines a second maximum spectral amplitude in the upper band where the result of block 1402 is indicated as max low2 and the result of block 1404 is indicated as max_high. Then, as illustrated in block 1406, the peak amplitude condition is true, when the second maximum spectral amplitude is greater than the first maximum spectral amplitude weighted by a predetermined number c3 being greater than or equal to 1 . c3 is preferably set to a value of 1.5 or to a value of 3 depending on different rates where, generally, values between 1 .0 and 5.0 have been proven as useful. Furthermore, as indicated in Fig. 14, the determination in blocks 1402 and 1404 takes place after shaping with the low-band shaping information, i.e., subsequent to the processing illustrated in block 804a and before the processing illustrated by block 804b or, with respect to Fig. 17, subsequent to block 1702 and before block 1704. In other embodiments, the peak amplitude condition 1 06 and, particularly, the procedure in Fig. 14, block 1402 is not determined from the smallest value in the lower frequency band, i.e., the lowest frequency value of the spectrum, but the determination of the first maximum spectral amplitude in the lower band is determined based on a portion of the lower band where the portion extends from a predetermined start frequency until a maximum frequency of the lower frequency band, where the predetermined start frequency is greater than a minimum frequency of the lower frequency band. In an embodiment, the predetermined start frequency is at least 10% of the lower frequency band above the minimum frequency of the lower frequency band or, in other embodiments, the predetermined start frequency is at a frequency being equal to half a maximum frequency of the lower frequency band within a tolerance range of plus or minus 10% of half the maximum frequency. Furthermore, it is preferred that the third predetermined number c3 depends on a bitrate to be provided by the quantizer/coder stage, so that the predetermined number is higher for a higher bitrate. In other words, when the bitrate that has to be provided by the quantizer and coder stage 806 is high, then c3 is high, while, when the bitrate is to be determined as low, then the predetermined number c3 is low. When the preferred equation in block 1406 is considered, it becomes clear that the higher predetermined number c3 is, the peak spectral region is determined more rarely. When, however, c3 is small, then a peak spec-tral region where there are spectral values to be finally attenuated is determined more often. Blocks 1202, 1204, 1402, 1404 or 1302 and 1306 always determine a spectral amplitude. The determination of the spectral amplitude can be performed differently. One way of the determination of the spectral envelope is the determination of an absolute value of a spectral value of the real spectrum. Alternatively, the spectral amplitude can be a magnitude of a complex spectral value. In other embodiments, the spectral amplitude can be any power of the spectral value of the real spectrum or any power of a magnitude of a complex spectrum, where the power is greater than 1. Preferably, the power is an integer number, but powers of 1.5 or 2.5 additionally have proven to be useful. Preferably, nevertheless, powers of 2 or 3 are preferred. Generally, the shaper 804 is configured to attenuate at least one spectral value in the detected peak spectral region based on a maximum spectral amplitude in the upper fre-quency band and/or based on a maximum spectral amplitude in the lower frequency band. In other embodiments, the shaper is configured to determine the maximum spectral amplitude in a portion of the lower frequency band, the portion extending from a predetermined start frequency of the lower frequency band until a maximum frequency of the lower frequency band. The predetermined start frequency is greater than a minimum frequency of the lower frequency band and is preferably at least 10% of the lower frequency band above the minimum frequency of the lower frequency band or the predetermined start frequency is preferably at the frequency being equal to half of a maximum frequency of the lower frequency band within a tolerance of plus or minus 10% of half of the maximum frequency. The shaper furthermore is configured to determine the attenuation factor determining the additional attenuation, where the attenuation factor is derived from the maximum spectral amplitude in the lower frequency band multiplied by a predetermined number being greater than or equal to one and divided by the maximum spectral amplitude in the upper frequency band. To this end, reference is made to block 1602 illustrating the determination of a maximum spectral amplitude in the lower band (preferably after shaping, i.e., after block 804a in Fig. 10 or after block 1702 in Fig. 17). Furthermore, the shaper is configured to determine the maximum spectral amplitude in the higher band, again preferably after shaping as, for example, is done by block 804a in Fig. 10 or block 1702 in Fig. 17. Then, in block 1606, the attenuation factor fac is calculated as illustrated, where the predetermined number c3 is set to be greater than or equal to 1. In embodiments, c3 in Fig. 16 is the same predetermined number c3 as in Fig. 14. However, in other embodiments, c3 in Fig. 16 can be set different from c3 in Fig. 14. Additionally, c3 in Fig. 16 that directly influences the attenuation factor is also dependent on the bi-trate so that a higher predetermined number c3 is set for a higher bitrate to be done by the quantizer/coder stage 806 as illustrated in Fig. 8. Fig. 17 illustrates a preferred implementation similar to what is shown at Fig. 10 at blocks 804a and 804b, i.e., that a shaping with the low-band gain information applied to the spec-tral values above the border frequency such as fce!p is performed in order to obtain shaped spectral values above the border frequency and additionally in a following step 1704, the attenuation factor fac as calculated by block 1606 in Fig. 16 is applied in block 1704 of Fig. 17. Thus, Fig. 17 and Fig. 10 illustrate a situation where the shaper is configured to shape the spectral values in the detected spectral region based on a first weighting opera-tion using a portion of the shaping information for the lower frequency band and a second subsequent weighting operation using an attenuation information, i.e., the exemplary attenuation factor fac. In other embodiments, however, the order of steps in Fig. 17 is reversed so that the first weighting operation takes place using the attenuation information and the second subsequent weighting information takes place using at least a portion of the shaping information for the lower frequency band. Or, alternatively, the shaping is performed using a single weighting operation using a combined weighting information depending and being derived from the attenuation information on the one hand and at least a portion of the shaping information for the lower frequency band on the other hand. As illustrated in Fig. 17, the additional attenuation information is applied to all the spectral values in the detected peak spectral region. Alternatively, the attenuation factor is only applied to, for example, the highest spectral value or the group of highest spectral values, where the members of the group can range from 2 to 10, for example. Furthermore, em-bodiments also apply the attenuation factor to all spectral values in the upper frequency band for which the peak spectral region has been detected by the detector for a time frame of the audio signal. Thus, in this embodiment, the same attenuation factor is applied to the whole upper frequency band when only a single spectral value has been determined as a peak spectral region. When, for a certain frame, no peak spectral region has been detected, then the lower frequency band and the upper frequency band are shaped by the shaper without any additional attenuation. Thus, a switching over from time frame to time frame is performed, where, depending on the implementation, some kind of smoothing of the attenuation in-formation is preferred. Preferably, the quantizer and encoder stage comprise a rate loop processor as illustrated in Fig. 15a and Fig. 15b. In an embodiment, the quantizer and coder stage 806 comprises a global gain weighter 1502, a quantizer 1504 and an entropy coder such as an arithmetic or Huffman coder 1506. Furthermore, the entropy coder 1506 provides, for a certain set of quantized values for a time frame, an estimated or measured bitrate to a controller 1508. The controller 1508 is configured to receive a loop termination criterion on the one hand and/or a predetermined bitrate information on the other hand. As soon as the controller 1508 determines that a predetermined bitrate is not obtained and/or a termination criterion is not fulfilled, then the controller provides an adjusted global gain to the global gain weighter 1502. Then, the global gain weighter applies the adjusted global gain to the shaped and attenuated spectral lines of a time frame. The global gain weighted output of block 1502 is provided to the quantizer 1504 and the quantized result is provided to the entropy encoder 1506 that once again determines an estimated or measured bitrate for the data weighted with the adjusted global gain. In case the termination criterion is fulfilled and/or the predetermined bitrate is fulfilled, then the encoded audio signal is output at output line 814. When, however, the predetermined bitrate is not obtained or a termination criterion is not fulfilled, then the loop starts again. This is illustrated in more detail in Fig. 15b. When the controller 1508 determines that the bitrate is too high as illustrated in block 1510, then a global gain is increased as illustrated in block 1512. Thus, all shaped and attenuated spectral lines become smaller since they are divided by the increased global gain and the quantizer then quantizes the smaller spectral values so that the entropy cod-er results in a smaller number of required bits for this time frame. Thus, the procedures of weighting, quantizing, and encoding is performed with the adjusted global gain as illustrated in block 1514 in Fig. 15b, and, then, once again it is determined whether the bitrate is too high. If the bitrate is still too high, then once again blocks 1512 and 1514 are performed. When, however, it is determined that the bitrate is not too high, the control pro-ceeds to step 1516 that outlines, whether a termination criterion is fulfilled. When the termination criterion is fulfilled, the rate loop is stopped and the final global gain is additionally introduced into the encoded signal via an output interface such as the output interface 1014 of Fig. 10. When, however, it is determined that the termination criterion is not fulfilled, then the global gain is decreased as illustrated in block 1518 so that, in the end, the maximum bitrate allowed is used. This makes sure that time frames that are easy to encode are encoded with a higher precision, i.e., with less loss. Therefore, for such instances, the global gain is decreased as illustrated in block 1518 and step 1514 is performed with the decreased global gain and step 1510 is performed in order to look whether the resulting bitrate is too high or not. Naturally, the specific implementation regarding the global gain increase or decrease increment can be set as required. Additionally, the controller 1508 can be implemented to either have blocks 1510, 1512 and 1514 or to have blocks 1510, 1516, 1518 and 1514. Thus, depending on the implementation, and also depending on the starting value for the global gain, the procedure can be such that, from a very high global gain it is started until the lowest global gain that still fulfills the bitrate requirements is found. On the other hand, the procedure can be done in such a way in that it is started from a quite low global gain and the global gain is increased until an allowable bitrate is obtained. Additionally, as illustrated in Fig. 15b, even a mix between both procedures can be applied as well. Fig. 10 illustrates the embedding of the inventive audio encoder consisting of blocks 802, 804a, 804b and 806 within a switched time domain/frequency domain encoder setting. Particularly, the audio encoder comprises a common processor. The common processor consists of an ACELP/TCX controller 1004 and the band limiter such as a resampler 1006 and an LPC analyzer 808. This is illustrated by the hatched boxes indicated by 1002. Furthermore, the band limiter feeds the LPC analyzer that has already been discussed with respect to Fig. 8. Then, the LPC shaping information generated by the LPC analyzer 808 is forwarded to a CELP coder 1008 and the output of the CELP coder 1008 is input into an output interface 1014 that generates the finally encoded signal 1020. Furthermore, the time domain coding branch consisting of coder 1008 additionally comprises a time domain bandwidth extension coder 1010 that provides information and, typically, paramet-ric information such as spectral envelope information for at least the high band of the full band audio signal input at input 1001. Preferably, the high band processed by the time domain band width extension coder 1010 is a band starting at the border frequency that is also used by the band limiter 1006. Thus, the band limiter performs a low pass filtering in order to obtain the lower band and the high band filtered out by the low pass band limiter 006 is processed by the time domain band width extension coder 1010. On the other hand, the spectral domain or TCX coding branch comprises a time-spectrum converter 1012 and exemplarily, a tonal mask as discussed before in order to obtain a gap-filling encoder processing. Then, the result of the time-spectrum converter 1012 and the additional optional tonal mask processing is input into a spectral shaper 804a and the result of the spectral shaper 804a is input into an attenuator 804b. The attenuator 804b is controlled by the detector 802 that performs a detection either using the time domain data or using the output of the time-spectrum convertor block 1012 as illustrated at 1022. Blocks 804a and 804b together implement the shaper 804 of Fig. 8 as has been discussed previously. The result of block 804 is input into the quantizer and coder stage 806 that is, in a certain embodiment, controlled by a predetermined bitrate. Additionally, when the predetermined numbers applied by the detector also depend on the predetermined bitrate, then the predetermined bitrate is also input into the detector 802 (not shown in Fig. 10). Thus, the encoded signal 1020 receives data from the quantizer and coder stage, control information from the controller 1004, information from the CELP coder 1008 and information from the time domain bandwidth extension coder 1010. Subsequently, preferred embodiments of the present invention are discussed in even more detail. An option, which saves interoperability and backward compatibility to existing implementations is to do an encoder-side pre-processing. The algorithm, as explained subsequently, analyzes the MDCT spectrum. In case significant signal components below fCELp are present and high peaks above fcELP are found, which potentially destroy the coding of the complete spectrum in the rate loop, these peaks above !CELP are attenuated. Although the attenuation can not be reverted on decoder-side, the resulting decoded signal is perceptually significantly more pleasant than before, where huge parts of the spectrum were ze-roed out completely. The attenuation reduces the focus of the rate loop on the peaks above fCEi.p and allows that significant low-frequency MDCT coefficients survive the rate loop. The following algorithm describes the encoder-side pre-processing: 1 ) Detection of low-band content (e.g. 1 102): The detection of low-band content analyzes, whether significant low-band signal portions are present. For this, the maximum amplitude of the MDCT spectrum below and above fCELP are searched on the MDCT spectrum before the application of inverse LPC shape gains. The search procedure returns the following values: a) max_low_pre: The maximum MDCT coefficient below fcELP, evaluated on the spectrum of absolute values before the application of inverse LPC shaping gains b) max_high_pre: The maximum MDCT coefficient above fCELP, evaluated on the spectrum of absolute values before the application of inverse LPC shaping gains For the decision, the following condition is evaluated: Condition 1 : c-i * max Jow pre > max_high_pre If Condition 1 is true, a significant amount of low-band content is assumed, and the pre-processing is continued; If Condition 1 is false, the pre-processing is aborted. This makes sure that no damage is applied to high-band only signals, e.g. a sine-sweep when above Pseudo-code: max __low pre = 0 ; for (i=0; i max low^ pre) { max_low_pre = tmp; } } max _high_pre = 0 ; for (i=0; i max high pre ) { max_high_pre = tmp; } } if (ci * max__low_pre > max_high_pre ) { / * continue with pre-proces s ing * / } where XM is the MDCT spectrum before application of the inverse LPC gain shaping, LJCX is the number of M DCT coefficients up to CELP LTCX(B > is the number of M DCT coefficients for the full M DCT spectrum In an example implementation ci is set to 16, and fabs returns the absolute value. ) Evaluation of peak-distance metric (e.g. 1 104): A peak-distance metric analyzes the impact of spectral peaks above fcELP on the arithmetic coder. Thus, the maximum amplitude of the MDCT spectrum below and above fCEi_p are searched on the MDCT spectrum after the application of inverse LPC shaping gains, i.e. in the domain where also the arithmetic coder is applied. In addition to the maximum amplitude, also the distance from fCF.i.p is evaluated. The search procedure returns the following values: a) maxjow: The maximum MDCT coefficient below fcELP. evaluated on the spectrum of absolute values after the application of inverse LPC shaping gains b) distjow: The distance of maxjow from fCELP c) max_high: The maximum MDCT coefficient above fCEL . evaluated on the spectrum of absolute values after the application of inverse LPC shaping gains d) dist_high: The distance of max_high from fCEi.p For the decision, the following condition is evaluated: Condition 2: c2 * distjiigh * max_high > distjow * maxjow If Condition 2 is true, a significant stress for the arithmetic coder is assumed, due to either a very high spectral peak or a high frequency of this peak. The high peak will dominate the coding-process in the Rate loop, the high frequency will penalize the arithmetic coder, since the arithmetic coder always runs from low to high frequencies, i.e. higher frequencies are inefficient to code. If Condition 2 is true, the pre-processing is continued. If Condition 2 is false, the pre-processing is aborted. max_low = 0; dist_low = 0 ; for (1=0; i max_low) { max low = tmp; ciist low = i ; max_high = 0 ; dist_high = 0; for(i=0; i; i++) { tmp = fabs (1„{LTcx iCELP) + i) ) ; if (tmp > max___high) { max __high - tmp; dist high = i ; if(c2 * dist_high * max high > dist low * max__low) ! /* continue with pre-processing */ where XM is the MDCT spectrum after application of the inverse LPC gain shaping, LTCX(CELP> is the number of MDCT coefficients up to fCELP LJCX is the number of MDCT coefficients for the full DCT spectrum In an example implementation c2 is set to 4. Comparison of peak-amplitude (e.g. 1 106): Finally, the peak-amplitudes in psycho-acoustically similar spectral regions are compared. Thus, the maximum amplitude of the MDCT spectrum below and above fcELP are searched on the MDCT spectrum after the application of inverse LPC shaping gains. The maximum amplitude of the MDCT spectrum below fCELp is not searched for the full spectrum, but only starting at f|0W > 0 Hz. This is to discard the lowest frequencies, which are psycho-acoustica!ly most important and usually have the highest amplitude after the application of inverse LPC shaping gains, and to only compare components with a similar psycho-acoustical importance. The search procedure returns the following values: a) max_low2: The maximum MDCT coefficient below fCFi p. evaluated on the spectrum of absolute values after the application of inverse LPC shaping gains starting b) max_high: The maximum MDCT coefficient above fCFi p. evaluated on the spectrum of absolute values after the application of inverse LPC shaping gains For the decision, the following condition is evaluated: Condition 3: max_high > c3 * max_low2 If condition 3 is true, spectral coefficients above fCe.p are assumed, which have significantly higher amplitudes than just below fCEi_p, and which are assumed costly to encode. The constant c3 defines a maximum gain, which is a tuning parameter. If Condition 2 is true, the pre-processing is continued. If Condition 2 is false, the pre-processing is aborted. Pseudo-code: max iow2 = 0 ; for (i=Llow; i< TCx{ } ; tmp = fabs (Xu (i) ) ; if (tmp > max_low2 } { max_low2 = tmp; } max_high = 0; for (i=0; i max high) { max high = tmp; } } if (max_high > c3 * max_low2 ) { /* continue with pre-processing */ } where L|0W is a offset corresponding to f|0W X M is the MDCT spectrum after application of the inverse LPC gain shaping, LrcxiCELP) is the number of MDCT coefficients up to I EIP LTCX(BW) is the number of MDCT coefficients for the full MDCT spectrum In an example implementation f|0W is set to LTCx /2. In an example implementation c3 is set to 1.5 for low bitrates and set to 3.0 for high bitrates. 4) Attenuation of high peaks above fCELP (e.g. Figs. 16 and 17): If condition 1 -3 are found to be true, an attenuation of the peaks above fcELP is applied. The attenuation allows a maximum gain c3 compared to a psycho- acousticaily similar spectral region. The attenuation factor is calculated as follows: attenuation_factor = c3 * max_low2 / max_high The attenuation factor is subsequently applied to all MDCT coefficients above fcELP- 5) Pseudo-code: if ( ( Ci * max__low__pre > max_high_pre ) & & ( C2 * di st_high * max_high > cli st low * max low) && (max^high > c3 * max_low2) } { fac = C3 * max__iow2 / max_high ; for ( i = LTCX ( CELP ) ; i< LTCX i BW) ; { XM ( ± ) = XM ( i ) * fac ; } } where X M is the MDCT spectrum after application of the inverse LPC gain shaping, LTcx{CELP) is the number of M DCT coefficients up to icup LTcx2 = w + 1 else j = [64/(64 - r)J , W] = w + 1 , = w 2 = 0 for = o,... ,63 { if j'mod i≠0 then = else w = ¾> 1 = 1 + 1 } } The remaining MDCT coefficients above the CELP frequency range (if any) are multiplied by the reciprocal of the last LPC shaping gain: 5.3.3.2.4 Adaptive low frequency emphasis 5.3,3.2.4.1 General Principle The purpose of the adaptive low-frequency emphasis and de-emphasis (ALFE) processes is to improve the subjective performance of the frequency-domain TCX codec at low frequencies. To this end, the low-frequency MDCT spectral lines are amplified prior to quantization in the encoder, thereby increasing their quantization SNR, and this boosting is undone prior to the inverse MDCT process in the internal and external decoders to prevent amplification artifacts. There are two different ALFE algorithms which are selected consistently in encoder and decoder based on the choice of arithmetic coding algorithm and bit-rate. ALFE algorithm 1 is used at 9.6 kbps (envelope based arithmetic coder) and at 48 kbps and above (context based arithmetic coder). ALFE algorithm 2 is used from 13.2 up to inch 32 kbps. In the encoder, the ALFE operates on the spectral lines in vector x [ ] directly before (algorithm 1) or after (algorithm 2) every MDCT quantization, which runs multiple times inside a rate-loop in case of the context based arithmetic coder (see subclause 5.3.3.2.8.1 ). 5.3.3.2.4.2 Adaptive emphasis algorithm 1 ALFE algorithm 1 operates based on the LPC frequency-band gains, IpcGa i ns [ ] . First, the minimum and maximum of the first nine gains - the low-frequency (LF) gains - are found using comparison operations executed within a loop over the gain indices 0 to 8. Then, if the ratio between the minimum and maximum exceeds a threshold of 1/32, a gradual boosting of the lowest lines in x is performed such that the first line (DC) is amplified by (32 rain /max)0,3 and the 33rd line is not amplified: tmp = 32 * min if ( (max < trap} && (max > 0 ) 5 { fac = tmp = pow ( tmp / max , 1 /128 ) for (i = 31 ; i >= 0 ; i - 5 { /* gradual boosting of lowest .32 lines */ x [ i ] *= fac fac *= tmp Adaptive emphasis algorithm 2 ALFE algorithm 2, unlike algorithm 1 , does not operate based on transmitted LPC gains but is signaled by means of modifications to the quantized low-frequency (LF) MDCT lines. The procedure is divided into five consecutive steps: • Step 1 : first find first magnitude maximum at index i ma in lower spectral quarter (k I 4) utilizing invGain = llgra and modifying the maximum: xq [ i_max] += ( xq [ i_max ] < 0 ) ? -2 : 2 • Step 2: then compress value range of all x [ i] up to i_ max by requantizing all lines at k = 0 ... i_max— 1 as in the subclause describing the quantization, but utilizing invGain instead of gTcx as the global gain factor. • Step 3 : find first magnitude maximum below i_max (k = 0 .. . ^ " ^ ^) which is half as high if i_max > -1 using invGain = 4/gTCx and modifying the maximum: xq [ i_max ] += (xq [ i_ max ] < 0 ) ? -2 : 2 • Step 4: re-compress and quantize all x [ i ] up to the half-height i_max found in the previous step, as in step 2 · Step 5: finish and always compress two lines at the latest i max found, i.e. at k = i_ max+l , i_max+2, again utilizing invGain = 2lgTCX if the initial i_max found in step 1 is greater than -1 , or using invGain = lgrcx otherwise. All i__max are initialized to—1. For details please see AdaptLowFreqEmph { ) in tcx_utils_enc.c. 5.3.3.2.5 Spectrum noise measure in power spectrum For guidance of quantization in the TXC encoding process, a noise measure between 0 (tonal) and 1 (noiselike) is determined for each MDCT spectral line above a specified frequency based on the current transform's power spectrum. The power spectrum XP (k) is computed from the MDCT coefficients XM (k) and the MDST X s (k) coefficients on the same time-domain signal segment and with the same windowing operation: Xp (k) = Xli (k) + X'l (k) for k = 0..ί · - 1 (4) Each noise measure in noiseF!ags(k) is then calculated as follows. First, if the transform length changed (e.g. after a TCX transition transform following an ACELP frame) or if the previous frame did not use TCX20 coding (e.g. in case a shorter transform length was used in the last frame), all noiseFlags(k) up to ^TCX ~~ ^ are reset to zero. The noise measure start line k,larl is initialized according to the following table 1 . Table 1 : Initialization table of k„nr. in noise measure For ACELP to TCX transitions, kstarl is scaled by 1.25. Then, if the noise measure start line kslar( is less than I^J X - 6 , the noiseFlags(k) at and above ksiari are derived recursively from running sums of power spectral lines: A-+7 έ+ι Si k ) C( k ) - ^ X r, (i ) (5) i=k -l i=k- , Jl if s(k) > (1.75 - 0.5 · noiseFlagik)) - c(k) {hw) noiseFlagik) = < . for kstart..L x - 8 (6) [0 otherwise Furthennore, every time noiseFlags(k) is given the value zero in the above loop, the variable lastTone is set to k. The upper 7 lines are treated separately since s(k) cannot be updated any more ( c(k) , however, is computed as above): noiseFlag = j1 ? ^ " 8>≥ ~ ^seF!agsik))■ ) ^ LM _7,. M _2 . (7) [0 otherwise The uppermost line at k = - 1) = 1 . Finally, if the above variable lastTone (which was initialized to zero) is greater than zero, then n o is eF lags {lastTone + 1) = 0 . Note that this procedure is only carried out in TCX20, not in other TCX modes ( noiseFlags(k) = 0 for k = 0. - 1 ). 5.3.3.2.6 Low pass factor detector A low pass factor c!pj- is determined based on the power spectrum for all bitrates below 32.0 kbps. Therefore, the power spectrum X P (A:) is compared iteratively against a threshold t[pj- for all k = - 1... 12 , where t!pf = 32.0 for regular MDCT windows and tjp^ = 64.0 for ACELP to MDCT transition windows. The iteration stops as soon as X p (k) > tjpf . The low pass factor C/pf determines as ctp = 0.3 - Cjpf^prev + 0.7 - {k + 1) / ύγςχ , where cjp _ prev is the last determined low pass factor. At encoder startup, cipf prev is set to 1.0. The low pass factor cipf is used to determine the noise filling stop bin (see subclause 5.3.3.2.10.2). 5.3.3.2.7 Uniform quantizer with adaptive dead-zone For uniform quantization of the MDCT spectrum X ^ after or before ALFE (depending on the applied emphasis algorithm, see subclause 5.3.3.2.4.1 ), the coefficients are first divided by the global gain gjcx (see subclause 5.3.3.2.8.1 .1 ), which controls the step-size of quantization. The results are then rounded toward zero with a rounding offset which is adapted for each coefficient based on the coefficient's magnitude (relative to gjcx ) and tonality (as defined by noiseFlagik) in subclause 5.3.3.2.5). For high-frequency spectral lines with low tonality and magnitude, a rounding offset of zero is used, whereas for all other spectral lines, an offset of 0.375 is employed. More specifically, the following algorithm is executed. Starting from the highest coded MDCT coefficient at index k = - 1 , we set (k) = 0 and decrement k by 1 as long as condition noiseFlagik) > 0 and \xM I g-p x < 1 evaluates to true. Then downward from the first line at index k'≥ 0 where this condition is not met (which is guaranteed since noiseFlagiG)— 0 ), rounding toward zero with a rounding offset of 0.375 and limiting of the resulting integer values to the range -32768 to 32767 is performed: mm. 1 M + 0.375 ,32767 XM (k) > 0 STCX XM {k) = (8) max M 0.375 -32768 XM {k) < 0 STCX with k = Ο.Λ' . Finally, all quantized coefficients of ¾fW at and above k =£j¾ are set to zero. 5.3.3.2.8 Arithmetic coder The quantized spectral coefficients are noiselessly coded by an entropy coding and more particularly by an arithmetic coding. The arithmetic coding uses 14 bits precision probabilities for computing its code. The alphabet probability distribution can be derived in different ways. At low rates, it is derived from the LPC envelope, while at high rates it is derived from the past context. In both cases, a harmonic model can be added for refining the probability model. The following pseudo-code describes the arithmetic encoding routine, which is used for coding any symbol associated with a probability model. The probability model is represented by a cumulative frequency table cum _freq[]. The derivation of the probability model is described in the following subclauses. /* global varibles */ low high bits to follow ar_encode (symbol, cum freq[]) { if (ari_first_symbol () ) { low = 0; high = 65535; bits to follow - 0; } range = high-low+1; if (symbol > 0) { high = low + ( ( range*cum_ fre [ symbol-1 ] ) »145 - 1; low +- { (range*cum _freq [ symbol-1] ) »1 ) - 1; for (;;! { if (high < 32768 ) ( write bit (0) ; while" ( bits_to_follow ) { writeJait (1) ; bits to follow-- } else if (low >= 32768 ) { write Jit (1) while ( bits to follow ) write_bit (0)7 bits to follow--; low 32768; high 32768; else if ( (low >= 16384) && (high < 49152) ) < bits^to _follow += 1; low -=~16384; high -= 16384; } else break; low += low; high += high+1; ) if ( ari_last_symbol ί ) ) /* flush bits */ if { low < 16384 } { write bit (0) ; while" j bits_to_follow > 0) { write_bit (1) ; bits_to_follow--; } ) else { write_bit (1) ; while ( bits_to_follow > 0) { write_bit (0) ; bits_to_follow— ; ! } ) The helper functions ari irst_symbol() and arijast_sym bol() detect the first symbol and the last symbol of the generated codeword respectively. 5.3.3.2.8.1 Context based arithmetic codec 5.3.3.2.8.1.1 Global gain estimator The estimation of the global gain gTCY for the TCX frame is performed in two iterative steps. The first esti™ mate considers a SNR gain of 6dB per sample per bit from SQ. The second estimate refines the estimate by taking into account the entropy coding. The energy of each block of 4 coefficients is first computed: 4 E[k] = X2 [4.k + i] i=0 (9) A bisection search is performed with a final resolution of 0.125dB: Initialization: Set fac = offset = 12,8 and target = 0.15 (target _bits - L/16) Iteration: Do the following block of operations 10 times 1 - fac=fac/2 2™ offset = offset -fac ¾ E k - o set if E k - offset > 0.3 2- ener = a[i], where 3- if(ener> target) then offset=offset+fac The first estimate of gain is then given by: gTCX = 0A5+ofJse, / 2 ( 10) 5.3.3.2.8.1 ,2 Rate-loop for constant bit rate and global gain In order to set the best gain gjcx within the constraints of used _bits < t rget _bits , convergence process of gfCX and used _bits is carried out by using following valuables and constants: WLb and Wub denote weights corresponding to the lower bound the upper bound, g fj and gin, denote gain corresponding to the lower bound the upper bound, and Lb _ found and Ub _ found denote flags indicating g and gyb is found, respectively. μ and η are variables with μ - max0,2.3 - 0.0025* r arget_bits) and η - 1/ μ . λ and v are constants, set as 10 and 0.96. After the initial estimate of bit consumption by arithmetic coding, stop is set 0 when target _bils is larger than used_bits , while stop is set as used_bits when used_bits is larger than t arget _bit . If stop is larger than 0, that means used_bits is larger than target _bits , gj'CX needs to be modified to be larger than the previous one and Lb _ found is set as TRUE, gib is set as the previous gfCX■ ^Lb 's set as WLb = stop - t arg et _bits + A , (1 1 ) When Ub _ found was set, that means used_bits was smaller than target _bits , g-p x is updated as an interpolated value between upper bound and lower bound. , STCX = (Sib■ wvb + gub■ wLh ) l[Wm + WLb ) , (12) Otherwise, that means Ub _ found is FALSE, gain is amplified as STCX = gTCX - Q + M - ((stop/ v) / t arget _bits-l)) , ( 13) with larger amplification ratio when the ratio of used _ bits (= stop) and target _bits is larger to accelerate to attain gyi, . If stop equals to 0, that means used _bits is smaller than target _bit , STCX should be smaller than the previous one and Ub _ found is set as 1 , Ub is set as the previous STCX and Wuh is set as = t arg ei _ Wfe - used _ bits + X , (14) If Lb _ found has been already set, gain is calculated as STCX = (Sib ■ Wub + gub■ WLb ) l{Wub + WLb ) , ( 15) otherwise, in order to accelerate to lower band gain g j b , gain is reduced as, STCX = STCX - Q - η · (ι - (used _bits - v) / t arg et _bits)) , (16) with larger reduction rates of gain when the ratio of used _ bits and t arget _bits is small. After above correction of gain, quantization is performed and estimation of used __bits by arithmetic coding is obtained. As a result, stop is set 0 when t argel _bits is larger than used _ bits , and is set as used _bits when it is larger than target _bits , If the loop count is less than 4, either lower bound setting process or upper bound setting process is carried out at the next loop depending on the value stop . If the loop count is 4, the final gain gjCX an the quantized MDCT sequence X 'QMDCT(^) are obtained. 5.3.3.2.8.1 .3 Probability model derivation and coding The quantized spectral coefficients X are noiselessly encoded starting from the lowest-frequency coefficient and progressing to the highest-frequency coefficient. They are encoded by groups of two coefficients a and b gathering in a so-called 2-uip!e {a,b} . Each 2-tuple {a,b} is split into three parts namely, MSB, LSB and the sign. The sign is coded independently from the magnitude using uniform probability distribution. The magnitude itself is further divided in two parts, the two most significant bits (MSBs) and the remaining least significant bitplanes {LSBs, if applicable). The 2-tuples for which the magnitude of the two spectral coefficients is lower or equal to 3 are coded directly by the MSB coding. Otherwise, an escape symbol is transmitted first for signalling any additional bit plane. The relation between 2-tuple, the individual spectral values a and b of a 2-tuple, the most significant bit planes m and the remaining least significant bit planes, r, are illustrated in the example in figure 1. In this example three escape symbols are sent prior to the actual value m, indicating three transmitted least significant bit planes Figure 1 : Example of a coded pair (2-tuple) of spectral values a and b and their representation as m and r. The probability model is derived from the past context. The past context is translated on a 12 bits-wise index and maps with the lookup table ari_context_lookup [] to one of the 64 available probability models stored in ari cf nfj. The past context is derived from two 2-tuples already coded within the same frame. The context can be derived from the direct neighbourhood or located further in the past frequencies. Separate contexts are maintained for the peak regions (coefficients belonging to the harmonic peaks) and other (non-peak) regions according to the harmonic model. If no harmonic model is used, only the other (non-peak) region context is used. The zeroed spectral values lying in the tail of spectrum are not transmitted. It is achieved by transmitting the index of last non-zeroed 2-tuple. If harmonic model is used, the tail of the spectrum is defined as the tail of spectrum consisting of the peak region coefficients, followed by the other (non-peak) region coefficients, as this definition tends to increase the number of trailing zeros and thus improves coding efficiency. The number of samples to encode is computed as follows: lastnz = 2( max {(X[ip[2k]] + X[ip[2k + !]]) > O}) + 2 ( 17) Q≤k0) save _bit (X[al i]>0?0:l) if (bl>0 ) savej3.it (X [bl_i ] >0?0 : 1 ) ; /* MSB encoding */ while (al > 3 M bl > 3) { pki = ari_context_lookup [t+1024*esc_nb] ; /* write escape codeword */ ari encode (17, ari cf m[pki]); a1>>=]. bl >>==!; levl++ esc nb = mill (levl , 3 ) ; } pki - ari_ context lookup [t H024 *esc nb] ari encode (al+4*bl, ari cf m[pki'J); /* l,SB encoding */ for ( lev-0 ; lev>lev) Si ) ; write bit_end ( (b>>lev) si ) } /•check budget* / if (nbbits>target_bits) { ari restore states ( ) ; break ) cu da e conte t ( a , b, al , bl , c , pi , ) } write sign bits(); I The helper functions ari_save_slates() and orij"estore_states() are used for saving and restoring the arithmetic coder states respectively. It allows cancelling the encoding of the last symbols if it violates the bit budget. Moreover and in case of bit budget overflow, it is able to fill the remaining bits with zeros till reaching the end of the bit budget or till processing lastnz samples in the spectrum. The other helper functions are described in the following subclauses. 5.3.3.2.8.1.4 Get next coefficient (a,p, Idx) = get_next _coeff (pi, hi, lastnz) If ( ( ii [ 0 ] ≥ lastnz - min(#pi, lastnz) 5 or (ii[l] < min(#pi, lastnz) and pi [ii [ 1] ] < hi[ii[0]])) then { p=l idx=ii [1] a=pi[ii[l] ] } else { p=0 idx=iifO] + #pi a= i[ii[0]] } ii[p]=ii[p] + 1 The ii[0] and ii[l] counters are initialized to 0 at the beginning of ari_context_encode() (and ari context decodeQ in the decoder). 5.3.3.2.8.1.5 Context update The context is updated as described by the following pseudo-code. It consists of the concatenation of two 4 bit- wise context elements. if { p\≠ p25 { c[pl] = 24 -(c[/7l]Al5) + t } if ( mod(Wx2,2) == 1 ; { t = l + 2|&/2j(l + |ft/4j) if ( t >13 ) /=12 + min(l + ^/8j,3) c[p2] = 24-(c[p2]Al5)+t ) } else { c[p\ v p2} = \6- (c[p\ v p2~ 15) if ! esc jib < 2 ) else c\p\ v p2] = c[pl v p2] + \2 + esc jib 5.3.3,2.8.1.6 Get context The final context is amended in two ways; t = c[pl v p2] i f mm(idxl, idx2) > L 1 2 then r = i + 256 if target_bit s > 400 then 5 t = i + 5 l2 The context t is an index from 0 to 1023, 5.3.3.2.8.1 .7 Bit consumption estimation The bit consumption estimation of the context-based arithmetic coder is needed for the rate-loop optimization 1 0 of the quantization. The estimation is done by computing the bit requirement without calling the arithmetic coder. The generated bits can be accurately estimated by: cum_freq= arith_cf_m[pki] +m proba*= cum freq[0]- cum_freq[l] nlz=norm_l (proba) /*get the number of leading zero * / 1 5 nbits=nlz proba>>=14 where proba is an integer initialized to 16384 and m is a MSB symbol. 5.3.3.2.8.1 .8 Harmonic model 20 For both context and envelope based arithmetic coding, a harmonic model is used for more efficient coding of frames with harmonic content. The model is disabled if any of the following conditions apply: - The bit-rate is not one of 9.6, 13.2, 16.4, 24.4, 32, 48 kbps. - The previous frame was coded by ACELP. - Envelope based arithmetic coding is used and the coder type is neither Voiced nor Generic. 25 - The single-bit harmonic model flag in the bit-stream in set to zero. When the model is enabled, the frequency domain interval of harmonics is a key parameter and is commonly analysed and encoded for both flavours of arithmetic coders. 5.3.3.2.8.1 .8.1 Encoding of Interval of harmonics When pitch lag and gain are used for the post processing, the lag parameter is utilized for representing the 30 interval of harmonics in the frequency domain. Otherwise, normal representation of interval is applied. 5.3.3.2.8.1 .8.1 .1 Encoding interval depending on time domain pitch lag If integer part of pitch lag in time domain dinl is less than the frame size of MDCT LTCX , frequency domain interval unit (between harmonic peaks corresponding to the pitch lag) Ty, f with 7 bit fractional accuracy is given by c T _ (2 · LTCX ' RES _ MAX) ' 2 ? °ϋ I UNIT - i ———^ (fl int ■ res d fr ) (18) where d jr denotes the fractional part of pitch lag in time domain, res _ max denotes the max number of allowable fractional values whose values are either 4 or 6 depending on the conditions. Since TUN/T has limited range, the actual interval between harmonic peaks in the frequency domain is coded 40 relatively to 7^w/?. using the bits specified in table 2. Among candidate of multiplication factors, RatioQ given in the table 3 or table 4, the multiplication number is selected that gives the most suitable harmonic interval of MDCT domain transform coefficients. Imkx = (Tlmr + 26 ) / 27 - 2 (19) 45 TMDCT = L4 · TUNIT■ Rati (lndexBmdwk!lh , lndexT , Index MUL (20) Table 2: Number of bits for specifying the multiplier depending on Indexj Table 3: Candidates of multiplier in the order of IndexMUL depending on IndexT (NB) Table 4: Candidates of multiplier in the order of depending on IndexT (WB) Inde. 0 3 4 5 6 7 8 9 10 1 1 12 13 14 15 16 18 19 20 21 22 23 24 25 26 27 28 30 32 34 36 38 40 1 1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 44 48 54 60 68 78 r _ 80o 2 1.5 2 2.5 3 4 5 6 7 8 9 10 12 14 16 18 22 24 26 28 30 32 34 36 38 40 42 44 48 52 54 68 3 1 1.5 2 2.5 3 4 5 6 7 8 9 10 1 1 12 13 14 15 18 20 22 24 26 28 30 32 34 36 40 44 48 I 54 4 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 9 10 11 12 13 14 15 16 18 20 22 24 26 28 34 40 41 5 1 1.5 2 2.5 3 3.5 4 4.5 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22. 24 25 27 28 30 35 5 6 0.5 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 7 8 9 10 1 2 2.5 3 4 5 6 7 8 9 10 12 15 16 18 27 8 1 1.5 2 2,5 3 3.5 4 5 6 8 10 15 18 22 24 26 9 1 1.5 2 2.5 3 3.5 4 5 6 8 10 12 13 14 18 21 10 0.5 1 1.5 2 2.5 3 4 5 6 8 9 1 1 12 13. 16 20 5 1 1 0.5 1 ,5 2 2.5 3 4 5 6 7 8 10 1 1 12 14 20 12 0.5 1 1.5 2 2.5 3 4 4.5 6 7.5 9 10 12 14 15 18 13 0.5 1 1 ,2 1 ,5 1 ,7 2 2,5 3 3,5 4 4,5 5 6 8 9 14 5 5 14 0.5 1 2 4 - - - - - - - - - - - - 15 1 1.5 2 4 - - - - - - - - - - - 1 6 1 2 3 4 - - - - - - - - - - - - 5.3.3.2.8.1 .8.1 .2 Encoding interval without depending on time domain pitch lag When pitch lag and gain in the time domain is not used or the pitch gain is less than or equals to 0.46, normal encoding of the interval with un-equal resolution is used. Unit interval of spectral peaks T NiT is coded as ' UNIT = index + base - 2Kes - Was , (21) and actual interval TMDCT is represented with fractional resolution of Res as R MDCT - '■ NIT 1 1 (22) Each paramter is shown in table 5, where "small size" means when frame size is smaller than 256 of the target bit rates is less than or equal to 150. Table 5: Un-equal resolution for coding of (0<= index < 256) 5.3.3.2.8.1 .8.2 Void 5.3.3.2.8.1 .8.3 Search for interval of harmonics In search of the best interval of harmonics, encoder tries to find the index which can maximize the weighted sum EpER10D of the peak part of absolute MDCT coefficients. EABSM (k) denotes sum of 3 samples of absolute value of MDCT domain transform coefficients as ¾™W =∑« ¾(i + i- l)) (23) (24) where num _peak is the maximum number that [n · TMDCT J reaches the limit of samples in the frequency domain. In case interval does not rely on the pitch lag in time domain, hierarchical search is used to save computational cost. If the index of the interval is less than 80, periodicity is checked by a coarse step of 4. After getting the best interval, finer periodicity is searched around the best interval from -2 to +2. If index is equal to or larger than 80, periodicity is searched for each index. 5.3.3.2.8.1 ,8.4 Decision of harmonic model At the initial estimation, number of used bits without harmonic model, used _ bits , and one with harmonic model, used _bitshm is obtained and the indicator of consumed bits IdicatorB are defined as idicaiorB = B,m lh B, nl » (25) B„o hm = max(stop, used (26) .¾,„ = max(stoplw! , used _ biisllm ) + Index _ bitslm , (27) where Index _bits/im denotes the additional bits for modelling harmonic structure, and stop and stop/lm indicate the consumed bits when they are larger than the target bits. Thus, the larger IdiccitorB , the more preferable to use harmonic model. Relative periodicity indicator^ is defined as the normalized sum of absolute values for peak regions of the shaped MDCT coefficients as indicator, = LM■ EPERI0D(TMDCr^mm)/^EABSM(n) , (28) ;l=l where ¾DCT max is the harmonic interval that attain the max value of E ERIOD■ When the score of periodicity of this frame is larger than the threshold as if ((indicator > 2) || {{abs{indicatorB ) < 2) & &(indicatojf1tn > 2.6)) , (29) this frame is considered to be coded by the harmonic model. The shaped MDCT coefficients divided by gain &TCX are quantized to produce a sequence of integer values of MDCT coefficients, XJQX hm > an& compressed by arithmetic coding with harmonic model. This process needs iterative convergence process (rate loop) to get g cx and XRCX HM with consumed bits BHM . At the end of convergence, in order to validate harmonic model, the consumed bits BNO HM by arithmetic coding with normal (non-harmonic) model for X-rcx hm 1S additionally calculated and compared with BHM . If BHM is larger than BNO HM , arithmetic coding of XJQX I„„ is revert to use normal model. BHN -BNO LLM can be used for residual quantization for further enhancements. Otherwise, harmonic model is used in arithmetic coding. In contrast, if the indicator of periodicity of this frame is smaller than or the same as the threshold, quantization and arithmetic coding are carried out assuming the normal model to produce a sequence of integer values of the shaped MDCT coefficients, XTCX „0 HM with consumed bits BNO /„„. After convergence of rate loop, consumed bits BHM by arithmetic coding with harmonic model for XT X N0 /,„, is calculated. If BNO HM is larger than BHM , arithmetic coding of XTCX „O!LM is switched to use harmonic model. Otherwise, normal model is used in arithmetic coding. 5.3.3.2.8.1 .9 Use of harmonic information in Context based arithmetic coding For context based arithmetic coding, all regions are classified into two categories. One is peak part and consists of 3 consecutive samples centered at U'1' ( U is a positive integer up to the limit) peak of harmonic peak of τυ , The other samples belong to normal or valley part. Harmonic peak part can be specified by the interval of harmonics and integer multiples of the interval. Arithmetic coding uses different contexts for peak and valley regions. For ease of description and implementation, the harmonic model uses the following index sequences: pi = (i e [0..½ - 1] : 3 U : τυ - 1 < ; < τυ + ] ) , (31 ) hi = (i e [0..LM - \] : i £ pi) , (32) ip = (pi, hi) , the concatenation of pi and hi . (33) In case of disabled harmonic model, these sequences are pi = ( ) , and hi = ip = (0,... , LM - l) . 5.3.3.2.8.2 Envelope based arithmetic coder In the MDCT domain, spectral lines are weighted with the perceptual model w(z) such that each line can be quantized with the same accuracy. The variance of individual spectral lines follow the shape of the linear predictor A ' (z) weighted by the perceptual model, whereby the weighted shape is S(z) = W(Z)A~ ] (Z) . W(z) is calculated by transforming q'^ to frequency domain LPC gains as detailed in subclauses 5.3.3,2.4.1 and 5.3.3.2.4.2. (z) is derived from ¾ after conversion to direct-form coefficients, and applying tilt compensation 1 - γζ~ ι , and finally transforming to frequency domain LPC gains. All other frequency-shaping tools, as well as the contribution from the harmonic model, shall be also included in this envelope shape S(z) . Observe that this gives only the relative variances of spectral lines, while the overall envelope has arbitrary scaling, whereby we must begin by scaling the envelope. 5.3.3.2,8.2.1 Envelope scaling We will assume that spectral lines xk are zero-mean and distributed according to the Laplace-distribution, whereby the probability distribution function is - exrf (34) 2b, The entropy and thus the bit-consumption of such a spectral line is bitsk = 1 + log2 2eb . However, this formula assumes that the sign is encoded also for those spectral lines which are quantized to zero. To compensate for this discrepancy, we use instead the approximation 0.035 bitsk = log2 2ebk + 0.15 + (35) ¾ J which is accurate for bk≥ 0.08 . We will assume that the bit-consumption of lines with b < 0.08 is bits = log2 (I .O224) which matches the bit-consumption at bk = 0.08 . For large bk > 255 we use the true entropy biisk = log2 (2e¾ ) for simplicity. 2 2 2 The variance of spectral lines is then σκ = 2bk . If sk is the k th element of the power of the envelope shape where γ is scaling coef- 2 ficieiit. In other words, sk describes only the shape of the spectrum without any meaningful magnitude and 2 γ is used to scale that shape to obtain the actual variance σκ· . Our objective is that when we encode all lines of the spectrum with an arithmetic coder, then the bit- Λ consumption matches a pre-defined level B , that is, B = ^T^ hi:xk . We can then use a bi-section algorithm to A-=0 determine the appropriate scaling factor γ such that the target bit-rate B is reached. Once the envelope shape bk has been scaled such that the expected bit-consumption of signals matching that shape yield the target bit-rate, we can proceed to quantizing the spectral lines. 5.3.3.2.8.2.2 Quantization rate loop Assume that ^. is quantized to an integer x such that the quantization interval is [x - 0.5, ¾ + 0.5] then the probability of a spectral line occurring in that interval is for | > 1 and for Lr^ | = 0 It follows that the bit-consumption for these two cases is in the ideal case \xk , » n l - - - log2 e - log2 1 - exp 01 + i -Llog2 e, xk≠0 bk •k JJ (38) lo ; l - exp| ¾ = 0. bk J By pre-computing the terms log2 , we can efficiently calculate the bit-consumption of the whole spectram The rate-loop can then be applied with a bi-section search, where we adjust the scaling of the spectral lines by a factor p , and calculate the bit-consumption of the spectram pxk , until we are sufficiently close to the desired bit-rate. Note that the above ideal-case values for the bit-consumption do not necessarily perfectly coincide with the final bit-consumption, since the arithmetic codec works with a finite-precision approximation. This rate-loop thus relies on an approximation of the bit-consumption, but with the benefit of a computationally efficient implementation. When the optimal scaling σ has been determined, the spectrum can be encoded with a standard arithmetic coder. A spectral line which is quantized to a value xk≠ 0 is encoded to the interval and xk = 0 is encoded onto the interval ¾ + 0.5 3, exp (40) The sign of ^.≠ 0 will be encoded with one further bit. Observe that the arithmetic coder must operate with a fixed-point implementation such that the above intervals are bit-exact across all platforms. Therefore all inputs to the arithmetic coder, including the linear predictive model and the weighting filter, must be implemented in fixed-point throughout the system 5.3.3.2.8.2.3 Probability mode! derivation and coding When the optimal scaling σ has been determined, the spectram can be encoded with a standard arithmetic coder. A spectral line which is quantized to a value xk≠ 0 is encoded to the interval and kk = 0 is encoded onto the inter The sign of xk ≠ 0 will be encoded with one further bit. 5.3.3.2.8.2.4 Harmonic mode! in envelope based arithmetic coding In case of envelope base arithmetic coding, harmonic model can be used to enhance the arithmetic coding. The similar search procedure as in the context based arithmetic coding is used for estimating the interval between harmonics in the MDCT domain. However, the harmonic model is used in combination of the LPC envelope as shown in figure 2. The shape of the envelope is rendered according to the information of the harmonic analysis. Harmonic shape at k in the frequency data sample is defined as /i - when T - 4≤k≤T + 4 , otherwise Q{k) = 1.0 , where τ denotes center position of U'" harmonics. h and σ are height and width of each harmonics depending on the unit interval as shown, h = 2.8 l .1 25 - exp(- 0.07 · TUDlT /2R" (45) σ = 0.5(2.6 - exp(- 0.05 . TMDCT /2R"| (46) Height and width get larger when interval gets larger. The spectral envelope S(k) is modified by the harmonic shape Q(k) at k as S(k) = S(k) - (l + gllarm -Q(k)) , (47) where gain for the harmonic components g^,arm is always set as 0.75 for Generic mode, and gtmrm ed from {0.6, 1.4, 4.5, 10.0} that minimizes Enom for Voiced mode using 2 bits, 0 Frequency [Hz] 6400 Figure 2: Example of harmonic envelope combined with LPC envelope used in envelope based arithmetic coding. 5.3.3.2.9 Global gain coding 5.3.3.2.9.1 Optimizing global gain The optimum global gain gop( is computed from the quantized and unquantized MDCT coefficients. For bit rates up to 32 kbps, the adaptive low frequency de-emphasis (see subclause 6.2.2.3.2) is applied to the quan-tized MDCT coefficients before this step. In case the computation results in an optimum gain less than or equal to zero, the global gain grcx determined before (by estimate and rate loop) is used. I Sop/ if go'pt > 0 \ STCX if So'p, < 0 5.3.3.2.9.2 Quantization of global gain For transmission to the decoder the optimum global gain gopt is quantized to a 7 bit index ITCi The dequantized global gain gp x is obtained as defined in subclause 6.2.2.3.3). 5.3.3.2.9.3 Residual coding The residual quantization is a refinement quantization layer refining the first SQ stage. It exploits eventual unused bits target _bits-nbbits, where nbbits is the number of bits consumed by the entropy coder. The residual quantization adopts a greedy strategy and no entropy coding in order to stop the coding whenever the bit-stream reaches the desired size. The residual quantization can refine the first quantization by two means. The first mean is the refinement of the global gain quantization. The global gain refinement is only done for rates at and above 13.2kbps. At most three additional bits is allocated to it. The quantized gain g cx s refined sequentially starting from n=0 and incrementing n by one after each following iteration: ifiSopi < hex ) then write bit (0) _ - l n-2~"" 2 / 28 STCX - STCX " I U else then write _bit{\) i n2 '""'" 2 i 2 S STCX - STCX * 1 Υ The second mean of refinement consists of re-quantizing the quantized spectnim line per line. First, the non-zeroed quantized lines are processed with a 1 bit residual quantizer: if(X[k] < X[k]) then write _bit(0) else then write _bit( ) Finally, if bits remain, the zeroed lines are considered and quantized with on 3 levels. The rounding offset of the SQ with deadzone was taken into account in the residual quantizer design: fac_ z = (1 - 0.375) - 0.33 if( \X[k] I 13200 (NFslarl ate < 13200 (55) kNFstop {min(?(0), round{c!pf ■ , if IGFis used mm(I}TCj, round(clp - - -LTCx )) , clse (56) 5.3.3.2.10.3 Noise Transition Width At each side of a noise filling segment a transition fadeout is applied to the inserted noise. The width of the transitions (number of bins) is defined as: 8 , if bitrate < 48000 4 + l2.8 - g£ypJ , if {titrate≥ 48000)Λ TCX20 A (HM = 0 V previous = ACELP) 4 + Ll2.8 - max(gir >,0.3125)J , if (bitrate≥ 48000)Λ TCX20 A (HM≠ 0 Λ previous≠ ACELP) 3 , if (bitrate≥ 48000) Λ TCXl 0 (57) where HM denotes that the harmonic model is used for the arithmetic codec and previous denotes the previous codec mode. 5.3.3.2.10.4 Computation of Noise Segments The noise filling segments are determined, which are the segments of successive bins of the MDCT spectram between kNFstart and kNF op LP for which all coefficients are quantized to zero. The segments are determined as defined by the following pseudo-code: k = kNFstarl while (k > kNFstart 12) and (xM (k ) = θ) do k = k - 1 k = k + l ^NFstart ~ k ,/ = o while (k < kNFsiop>LP ) { while (k < kNFslop _p ) and (xM (k)≠ θ) do k = k + 1 kNFo (j) = k while (k < kNFslop LP ) and {xM (k) = o) do k = k + kNFi (j) = k if {kNFQ (j) < kNFsl0PrLP ) then j = . + ! } nNF = J where k NFQ (j) and kNF\ (j) are the start and stop bins of noise filling segment j, and nNF is the number of segments. 5.3.3.2.10.5 Computation of Noise Factor The noise factor is computed from the unquantized MDCT coefficients of the bins for which noise filling is applied. If the noise transition width wNF is 3 or less bins, an attenuation factor is computed based on the energy of even and odd MDCT bins: J NFev NFodd For each segment an error value is computed from the unquantized MDCT coefficients, applying global gain, tilt compensation and transitions: B i weight for each segment is computed based on the width of the segment; kNFl {j) -~ kNF0 O WNF + 1 {wNF < 3) Λ (kNFl {j)~ kNF0{j) > 2wNF (kNFl (j) - kNF() (j)f (wNF < 3) A (kNFl (j)- kNF0{j)≤2wNF eNF (/) = (62) kNF[ (j) ~ kNF (./') - 7 [wNF > 3)Λ (kNFl (j) - kNF0 (j) > 12) 0.03515625(kNFl (j)- kNF0 (jf (wNF > 3)Λ (kNFl (j) - kNFQ (j) < 12) The noise factor is then computed as follows: 5.3.3.2.10.6 Quantization of Noise Factor For transmission the noise factor is quantized to obtain a 3 bit index: 1NF = min(Ll0.75 + 0.5 j 7) 5.3.3.2.1 1 Intelligent Gap Filling The Intelligent Gap Filling (IGF) tool is an enhanced noise filling technique to fill gaps (regions of zero values) in spectra. These gaps eiay occur due to coarse quantization in the encoding process where large portions of a given spectrum might be set to zero to meet bit constraints. However, with the IGF tool these missing signal portions are reconstructed on the receiver side (RX) with parametric information calculated the transmission side (TX). IGF is used only if TCX mode is active. Claims Audio encoder for encoding an audio signal having a lower frequency band and an upper frequency band, comprising: a detector (802) for detecting a peak spectral region in the upper frequency band of the audio signal; a shaper (804) for shaping the lower frequency band using shaping information for the lower band and for shaping the upper frequency band using at least a portion of the shaping information for the lower frequency band, wherein the shaper (804) is configured to additionally attenuate spectral values in the detected peak spectra! region in the upper frequency band; and a quantizer and coder stage (806) for quantizing a shaped lower frequency band and a shaped upper frequency band and for entropy coding quantized spectral values from the shaped lower frequency band and the shaped upper frequency band. Audio encoder of claim 1 , further comprising: a linear prediction analyzer (808) for deriving linear prediction coefficients for a time frame of the audio signal by analyzing a block of audio samples in the time frame, the audio samples being band-limited to the lower frequency band, wherein the shaper (804) is configured to shape the lower frequency band using the linear prediction coefficients as the shaping information, and wherein the shaper (804) is configured to use at least the portion of the linear prediction coefficients derived from the block of audio samples band-limited to the lower frequency band for shaping the upper frequency band in the time frame of the audio signal. Audio encoder of claim 1 or 2, wherein the shaper (804) is configured to calculate a plurality of shaping factors for a plurality of subbands of the lower frequency band using linear prediction coefficients derived from the lower frequency band of the audio signal, wherein the shaper (804) is configured to weight, in the lower frequency band, spectral coefficients in a subband of the lower frequency band using a shaping factor calculated for the corresponding subband, and to weight spectral coefficients in the upper frequency band using a shaping factor calculated for one of the subbands of the lower frequency band. Audio encoder of claim 3, wherein the shaper (804) is configured to weight the spectral coefficients of the upper frequency band using a shaping factor calculated for a highest subband of the lower frequency band, the highest subband having a highest center frequency among all center frequencies of subbands of the lower frequency band. Audio encoder of one of the preceding claims, wherein the detector (802) is configured to determine a peak spectral region in the upper frequency band, when at least one of a group of conditions is true, the group of conditions comprising at least the following: a low frequency band amplitude condition (1 102), a peak distance condition (1 104), and a peak amplitude condition (1 106). Audio encoder of claim 5, wherein the detector (802) is configured to determine, for the low-frequency band amplitude condition, a maximum spectral amplitude in the lower frequency band (1202); a maximum spectral amplitude in the upper frequency band (1204), wherein the low frequency band amplitude condition (1 02) is true, when the maximum spectral amplitude in the lower frequency band weighted by a predetermined number greater than zero is greater than the maximum spectral amplitude in the upper frequency band (1204). Audio encoder of claim 6, wherein the detector (802) is configured to detect the maximum spectral amplitude in the lower frequency band or the maximum spectral amplitude in the upper frequency band before a shaping operation applied by the shaper (804) is applied, or wherein the predetermined number is between 4 and 30. Audio encoder of one of claims 5 to 7, wherein the detector (802) is configured to determine, for the peak distance condition, a first maximum spectral amplitude in the lower frequency band (1206); a first spectral distance of the first maximum spectral amplitude from a border frequency between a center frequency of the lower frequency band (1302) and a center frequency of the upper frequency band (1304); a second maximum spectral amplitude in the upper frequency band (1306); a second spectral distance of the second maximum spectral amplitude from the border frequency to the second maximum spectral amplitude (1308), wherein the peak distance condition (1 104) is true, when the first maximum spectral amplitude weighted by the first spectral distance and weighted by a predetermined number being greater than 1 is greater than the second maximum spectral amplitude weighted by the second spectral distance (1310). Audio encoder of claim 8, wherein the detector (802) is configured to determine the first maximum spectral amplitude or the second maximum spectral amplitude subsequent to a shaping operation by the shaper (804) without the additional attenuation, or wherein the border frequency is the highest frequency in the lower frequency band or the lowest frequency in the upper frequency band, or wherein the predetermined number is between 1.5 and 8. 10. Audio encoder of one of claims 5 to 9, wherein the detector (802) is configured to determine a first maximum spectral amplitude in a portion of the lower frequency band (1402), the portion extending from a predetermined start frequency of the lower frequency band until a maximum frequency of the lower frequency band, the predetermined start frequency being greater than a minimum frequency of the lower frequency band, to determine a second maximum spectral amplitude in the upper frequency band (1404), wherein the peak amplitude condition (1 106) is true, when the second maximum spectral amplitude is greater than the first maximum spectral amplitude weighted by a predetermined number being greater than or equal to 1 (1406). 1 1. Audio encoder of claim 10, wherein the detector (802) is configured to determine the first maximum spectral amplitude or the second maximum spectral amplitude after a shaping operation applied by the shaper (804) without the additional attenuation, or wherein the predetermined start frequency is at least 10% of the lower frequency band above the minimum frequency of the lower frequency band or wherein the predetermined start frequency is at a frequency being equal to half a maximum frequency of the lower frequency band within a tolerance of plus/minus 10 percent of the half the maximum frequency, or wherein the predetermined number depends on a bitrate to be provided by the quantizer/coder stage, so that the predetermined number is higher for a higher bitrate, or wherein the predetermined number is between 1 .0 and 5.0. Audio encoder of one of claims 6 to 1 1 , wherein the detector (802) is configured to determine the peak spectral region only when at least two conditions out of the three conditions or the three conditions are true. Audio encoder of one of claims 6 to 12, wherein the detector (802) is configured to determine, as the spectral amplitude, an absolute value of spectral value of the real spectrum, a magnitude of a complex spectrum, any power of the spectral value of the real spectrum or any power of a magnitude of the complex spectrum, the power being greater than 1. Audio encoder of one of the preceding claims, wherein the shaper (804) is configured to attenuate at least one spectral value in the detected peak spectral region based on a maximum spectral amplitude in the upper frequency band or based on a maximum spectral amplitude in the lower frequency band. Audio encoder of claim 14, wherein the shaper (804) is configured to determine the maximum spectral amplitude in a portion of the lower frequency band, the portion extending from a predetermined start frequency of the lower frequency band until a maximum frequency of the lower frequency band, the predetermined start frequency being greater than a minimum frequency of the lower frequency band, wherein the predetermined start frequency is preferably at least 10% of the lower frequency band above the minimum frequency of the lower frequency band or wherein the predetermined start frequency is preferably at a frequency being equal to half a maximum frequency of the lower frequency band within a tolerance of plus/minus 10 percent of the half the maximum frequency. Audio encoder of one of claims 1 or 15, wherein the shaper (804) is configured to additionally attenuate the spectral values using an attenuation factor, the attenuation factor being derived from the maximum spectral amplitude in the lower frequency band (1602) multiplied (1606) by a predetermined number being greater than or equal to 1 and divided by the maximum spectral amplitude in the upper frequency band (1604). Audio encoder of one of the preceding claims, wherein the shaper (804) is configured to shape the spectral values in the detected peak spectral region based on: a first weighting operation (1702, 804a) using at least the portion of the shaping information for the lower frequency band and a second subsequent weighting operation (1704, 804b) using an attenuation information; or a first weighting operation using the attenuation information and a second subsequent weighting information using at least a portion of the shaping information for the lower frequency band, or a single weighting operation using a combined weighting information derived from the attenuation information and at least the portion of the shaping information for the lower frequency band. Audio encoder of claim 17, wherein the weighting information for the lower frequency band is a set of shaping factors, each shaping factor being associated with a subband of the lower frequency band, wherein the at least the portion of the weighting information for the lower frequency band used in the shaping operation for the higher frequency band is a shaping factor associated with a subband of the lower frequency band having a highest center frequency of all subbands in the lower frequency band, or wherein the attenuation information is an attenuation factor applied to the at least one spectral value in the detected spectral region or to ail the spectral values in the detected spectral region or to all spectra! values in the upper frequency band for which the peak spectral region has been detected by the detector (802) for a time frame of the audio signal, or wherein the shaper (804) is configured to perform the shaping of the lower and the upper frequency band without any additional attenuation when the detector (802) has not detected any peak spectral region in the upper frequency band of a time frame of the audio signal. Audio encoder of one of the preceding claims, wherein the quantizer and coder stage (806) comprises a rate loop processor for estimating a quantizer characteristic so that a predetermined bitrate of an entropy encoded audio signal is obtained. Audio encoder of claim 19, wherein the quantizer characteristic is a global gain, wherein the quantizer and coder stage (806) comprises: a weighter (1502) for weighting shaped spectral values in the lower frequency band and shaped spectral values in the upper frequency band by the same global gain, a quantizer (1504) for quantizing values weighted by the global gain; and an entropy coder (1506) for entropy coding the quantized values, wherein the entropy coder comprises an arithmetic coder or an Huffman coder. Audio encoder of one of the preceding claims, further comprising: a tonal mask processor (1012) for determining, in the upper frequency band, a first group of spectral values to be quantized and entropy encoded and a second group of spectral values to be parametrically coded by a gap-filling procedure, wherein the tonal mask processor is configured to set the second group of spectral values to zero values. 22. Audio encoder of one of the preceding claims, further comprising: a common processor (1002); a frequency domain encoder (1012, 802, 804, 806); and a linear prediction encoder (1008), wherein the frequency domain encoder comprises the detector (802), the shaper (804) and the quantizer and coder stage (806), and wherein the common processor is configured calculate data to be used by the frequency domain encoder and the linear prediction encoder. 23. Audio encoder of claim 22, wherein the common processor is configured to resample (1006) the audio signal to obtain a resampled audio signal band limited to the lower frequency band for a time frame of the audio signal, and wherein the common processor (1002) comprises a linear prediction analyzer (808) for deriving linear prediction coefficients for the time frame of the audio signal by analyzing a block of audio samples in the time frame, the audio samples being band-limited to the lower frequency band, or wherein the common processor (1002) is configured to control that the time frame of the audio signal is to be represented by either an output of the linear prediction encoder or an output of the frequency domain encoder. 24. Audio encoder of one of claims 22 to 23, wherein the frequency domain encoder comprises a time-to-frequency converter (1012) for converting a time frame of the audio signal into a frequency representation comprising the lower frequency band and the upper frequency band. 25. Method for encoding an audio signal having a lower frequency band and an upper frequency band, comprising: detecting (802) a peak spectral region in the upper frequency band of the audio signal; shaping (804) the lower frequency band of the audio signai using shaping information for the lower frequency band and shaping (1702) the upper frequency band of the audio signal using at least a portion of the shaping information for the lower frequency band, wherein the shaping of the upper frequency band comprises an additional attenuation (1704) of a spectral value in the detected peak spectral region in the upper frequency band. 26. Computer program for performing, when running on a computer or processor, the method of claim 25.