TECHNICAL FIELD
[0001] The present disclosure relates generally to the field of signal processing. More
particularly, the present disclosure relates to system and method for converting EEG signal to
speech.
BACKGROUND
[0002] Spoken language is a uniquely human trait. The human brain has evolved
computational mechanisms that decode highly variable acoustic inputs into meaningful
elements of language, such as phonemes and words. Yet for hundreds of thousands of
patients, including certain patients who suffer from paralysis, locked-in syndrome, Lou
Gehrig's disease, or other neurological diseases, the ability to communicate via spoken
language is lacking or impaired.
[0003] Motivations for this invention are the many neurological, trauma, and
cognitive stress conditions that can alter motor control and cognitive state and therefore alter
speech production and other sensorimotor activities by influencing the characteristics of the
vocal source, tract, and prosodics, as well as other motor components. Early, accurate
detection of such conditions aid in possible intervention and rehabilitation. Thus, simple noninvasive
biomarkers are desired for determining severity. Recently, there have been
significant efforts in the use of vocal biomarkers. Features may be extracted from speech and
compared to a library of such features for various disorders to diagnose or predict severity of
the disorder.
[0004] There is, therefore, a need in the art to provide a system and method that fulfils
the aforementioned needs and also addresses the occasional inefficacy available in the
devices and techniques of prior-art. Further, there is also a need to provide system and
method to convert EEG signal to speech that is cost efficient and easy to implement.
OBJECTS OF THE PRESENT DISCLSOURE
[0005] Some of the objects of the present disclosure, which at least one embodiment
herein satisfies are as listed herein below.
[0006] It is an object of the present disclosure to provide system and method to
convert EEG signal to speech.
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[0007] It is another object of the present disclosure to provide system and method to
convert EEG signal to speech that is cost efficient and easy to implement.
[0008] It is another object of the present disclosure to provide system and method to
convert EEG signal to speech that enables accessing of converted speech remotely.
[0009] It is another object of the present disclosure to provide system and method to
convert EEG signal to speech that enables speech impaired user to communicate with others.
SUMMMARY
[0010] The present disclosure relates generally to the field of signal processing. More
particularly, the present disclosure relates to system and method for converting EEG signal to
speech.
[0011] An aspect of the present disclosure relates to a system for converting an EEG
signal to speech, the system comprising: a processor coupled with a memory, the memory
storing instructions executable by the processor to: receive the EEG signal of a first user;
process the received EEG signal, wherein the received EEG signal is amplified, and
amplified signal is filtered to remove noise signals; convert filtered signal to an audio signal,
wherein the filtered signal is compared with one or more pre-defined signals stored in a first
database, and wherein each of the one or more pre-defined signals is associated with a
corresponding audio signal, and wherein based on comparison the filtered signals is
converted to the audio signal.
[0012] In an embodiment, the processor configured to transmit the converted audio
signal to an audio output device.
[0013] In an embodiment, the audio output device is associated with a computing
device associated with a second user.
[0014] In an embodiment, the EEG signal is acquired from one or more EEG sensors
placed at pre-defined position on body of the first user.
[0015] In an embodiment, the filtered signal is converted using a MATLAB, and
wherein the filtered signal is converted to corresponding text and the converted text is
converted to the audio signal.
[0016] In an embodiment, combination of plurality of converted audio signals forms a
speech.
[0017] Another aspect of the present disclosure relates to a method for converting an
EEG signal to speech, the method comprising: receiving, by a processor, the EEG signal of a
first user; processing, by the processor, the received EEG signal, wherein the received EEG
4
signal is amplified, and amplified signal is filtered to remove noise signals; converting, by the
processor, filtered signal to an audio signal, wherein the filtered signal is compared with one
or more pre-defined signals stored in a first database.
[0018] In an embodiment, the method comprises transmitting using the processor, the
converted audio signal to an audio output device.
[0019] In an embodiment, the method comprises converting the filtered signal by the
processor using a MATLAB, and wherein the filtered signal is converted to corresponding
text and the converted text is converted to the audio signal.
[0020] In an embodiment, the method comprises combination of plurality of
converted audio signals to form a speech.
BRIEF DESCRIPTION OF THE DRAWINGS
[0021] In the figures, similar components and/or features may have the same
reference label. Further, various components of the same type may be distinguished by
following the reference label with a second label that distinguishes among the similar
components. If only the first reference label is used in the specification, the description is
applicable to any one of the similar components having the same first reference label
irrespective of the second reference label.
[0022] FIG. 1 illustrates an exemplary network architecture in which or with which
proposed system can be implemented in accordance with an embodiment of the present
disclosure.
[0023] FIG. 2 illustrates an exemplary module diagram for converting EEG signal to
speech in accordance with an embodiment of the present disclosure.
[0024] FIG. 3 is a flow diagram illustrating a process for converting EEG signal to
speech in accordance with an embodiment of the present disclosure.
[0025] FIG. 4 illustrates an exemplary computer system in which or with which
embodiments of the present invention can be utilized in accordance with embodiments of the
present disclosure.
DETAILED DESCRIPTION
[0026] The following is a detailed description of embodiments of the disclosure
depicted in the accompanying drawings. The embodiments are in such detail as to clearly
communicate the disclosure. However, the amount of detail offered is not intended to limit
the anticipated variations of embodiments; on the contrary, the intention is to cover all
5
modifications, equivalents, and alternatives falling within the spirit and scope of the present
disclosure as defined by the appended claims.
[0027] In the following description, numerous specific details are set forth in order to
provide a thorough understanding of embodiments of the present invention. It will be
apparent to one skilled in the art that embodiments of the present invention may be practiced
without some of these specific details.
[0028] Embodiments of the present invention include various steps, which will be
described below. The steps may be performed by hardware components or may be embodied
in machine-executable instructions, which may be used to cause a general-purpose or specialpurpose
processor programmed with the instructions to perform the steps. Alternatively, steps
may be performed by a combination of hardware, software, and firmware and/or by human
operators.
[0029] Various methods described herein may be practiced by combining one or more
machine-readable storage media containing the code according to the present invention with
appropriate standard computer hardware to execute the code contained therein. An apparatus
for practicing various embodiments of the present invention may involve one or more
computers (or one or more processors within a single computer) and storage systems
containing or having network access to computer program(s) coded in accordance with
various methods described herein, and the method steps of the invention could be
accomplished by modules, routines, subroutines, or subparts of a computer program product.
[0030] If the specification states a component or feature “may”, “can”, “could”, or
“might” be included or have a characteristic, that particular component or feature is not
required to be included or have the characteristic.
[0031] As used in the description herein and throughout the claims that follow, the
meaning of “a,” “an,” and “the” includes plural reference unless the context clearly dictates
otherwise. Also, as used in the description herein, the meaning of “in” includes “in” and “on”
unless the context clearly dictates otherwise.
[0032] Exemplary embodiments will now be described more fully hereinafter with
reference to the accompanying drawings, in which exemplary embodiments are shown. These
exemplary embodiments are provided only for illustrative purposes and so that this disclosure
will be thorough and complete and will fully convey the scope of the invention to those of
ordinary skill in the art. The invention disclosed may, however, be embodied in many
different forms and should not be construed as limited to the embodiments set forth herein.
Various modifications will be readily apparent to persons skilled in the art. The general
6
principles defined herein may be applied to other embodiments and applications without
departing from the spirit and scope of the invention. Moreover, all statements herein reciting
embodiments of the invention, as well as specific examples thereof, are intended to
encompass both structural and functional equivalents thereof. Additionally, it is intended that
such equivalents include both currently known equivalents as well as equivalents developed
in the future (i.e., any elements developed that perform the same function, regardless of
structure). Also, the terminology and phraseology used is for the purpose of describing
exemplary embodiments and should not be considered limiting. Thus, the present invention is
to be accorded the widest scope encompassing numerous alternatives, modifications and
equivalents consistent with the principles and features disclosed. For purpose of clarity,
details relating to technical material that is known in the technical fields related to the
invention have not been described in detail so as not to unnecessarily obscure the present
invention.
[0033] Thus, for example, it will be appreciated by those of ordinary skill in the art
that the diagrams, schematics, illustrations, and the like represent conceptual views or
processes illustrating systems and methods embodying this invention. The functions of the
various elements shown in the figures may be provided through the use of dedicated
hardware as well as hardware capable of executing associated software. Similarly, any
switches shown in the figures are conceptual only. Their function may be carried out through
the operation of program logic, through dedicated logic, through the interaction of program
control and dedicated logic, or even manually, the particular technique being selectable by
the entity implementing this invention. Those of ordinary skill in the art further understand
that the exemplary hardware, software, processes, methods, and/or operating systems
described herein are for illustrative purposes and, thus, are not intended to be limited to any
particular named element.
[0034] Embodiments of the present invention may be provided as a computer program
product, which may include a machine-readable storage medium tangibly embodying thereon
instructions, which may be used to program a computer (or other electronic devices) to
perform a process. The term “machine-readable storage medium” or “computer-readable
storage medium” includes, but is not limited to, fixed (hard) drives, magnetic tape, floppy
diskettes, optical disks, compact disc read-only memories (CD-ROMs), and magneto-optical
disks, semiconductor memories, such as ROMs, PROMs, random access memories (RAMs),
programmable read-only memories (PROMs), erasable PROMs (EPROMs), electrically
erasable PROMs (EEPROMs), flash memory, magnetic or optical cards, or other type of
7
media/machine-readable medium suitable for storing electronic instructions (e.g., computer
programming code, such as software or firmware).A machine-readable medium may include
a non-transitory medium in which data may be stored and that does not include carrier waves
and/or transitory electronic signals propagating wirelessly or over wired connections.
Examples of a non-transitory medium may include, but are not limited to, a magnetic disk or
tape, optical storage media such as compact disk (CD) or digital versatile disk (DVD), flash
memory, memory or memory devices. A computer-program product may include code and/or
machine-executable instructions that may represent a procedure, a function, a subprogram, a
program, a routine, a subroutine, a module, a software package, a class, or any combination
of instructions, data structures, or program statements. A code segment may be coupled to
another code segment or a hardware circuit by passing and/or receiving information, data,
arguments, parameters, or memory contents. Information, arguments, parameters, data, etc.
may be passed, forwarded, or transmitted via any suitable means including memory sharing,
message passing, token passing, network transmission, etc.
[0035] Furthermore, embodiments may be implemented by hardware, software,
firmware, middleware, microcode, hardware description languages, or any combination
thereof. When implemented in software, firmware, middleware or microcode, the program
code or code segments to perform the necessary tasks (e.g., a computer-program product)
may be stored in a machine-readable medium. A processor(s) may perform the necessary
tasks.
[0036] Systems depicted in some of the figures may be provided in various
configurations. In some embodiments, the systems may be configured as a distributed system
where one or more components of the system are distributed across one or more networks in
a cloud computing system.
[0037] Each of the appended claims defines a separate invention, which for
infringement purposes is recognized as including equivalents to the various elements or
limitations specified in the claims. Depending on the context, all references below to the
"invention" may in some cases refer to certain specific embodiments only. In other cases it
will be recognized that references to the "invention" will refer to subject matter recited in one
or more, but not necessarily all, of the claims.
[0038] All methods described herein may be performed in any suitable order unless
otherwise indicated herein or otherwise clearly contradicted by context. The use of any and
all examples, or exemplary language (e.g., “such as”) provided with respect to certain
embodiments herein is intended merely to better illuminate the invention and does not pose a
8
limitation on the scope of the invention otherwise claimed. No language in the specification
should be construed as indicating any non-claimed element essential to the practice of the
invention.
[0039] Various terms as used herein are shown below. To the extent a term used in a
claim is not defined below, it should be given the broadest definition persons in the pertinent
art have given that term as reflected in printed publications and issued patents at the time of
filing.
[0040] The present disclosure relates generally to the field of signal processing. More
particularly, the present disclosure relates to system and method for converting EEG signal to
speech.
[0041] An aspect of the present disclosure relates to a system for converting an EEG
signal to speech, the system comprising: a processor coupled with a memory, the memory
storing instructions executable by the processor to: receive the EEG signal of a first user;
process the received EEG signal, wherein the received EEG signal is amplified, and
amplified signal is filtered to remove noise signals; convert filtered signal to an audio signal,
wherein the filtered signal is compared with one or more pre-defined signals stored in a first
database, and wherein each of the one or more pre-defined signals is associated with a
corresponding audio signal, and wherein based on comparison the filtered signals is
converted to the audio signal.
[0042] In an embodiment, the processor configured to transmit the converted audio
signal to an audio output device.
[0043] In an embodiment, the audio output device is associated with a computing
device associated with a second user.
[0044] In an embodiment, the EEG signal is acquired from one or more EEG sensors
placed at pre-defined position on body of the first user.
[0045] In an embodiment, the filtered signal is converted using a MATLAB, and
wherein the filtered signal is converted to corresponding text and the converted text is
converted to the audio signal.
[0046] In an embodiment, combination of plurality of converted audio signals forms a
speech.
[0047] Another aspect of the present disclosure relates to a method for converting an
EEG signal to speech, the method comprising: receiving, by a processor, the EEG signal of a
first user; processing, by the processor, the received EEG signal, wherein the received EEG
signal is amplified, and amplified signal is filtered to remove noise signals; converting, by the
9
processor, filtered signal to an audio signal, wherein the filtered signal is compared with one
or more pre-defined signals stored in a first database.
[0048] In an embodiment, the method comprises transmitting using the processor, the
converted audio signal to an audio output device.
[0049] In an embodiment, the method comprises converting the filtered signal by the
processor using a MATLAB, and wherein the filtered signal is converted to corresponding
text and the converted text is converted to the audio signal.
[0050] In an embodiment, the method comprises combination of plurality of
converted audio signals to form a speech.
[0051] FIG. 1 illustrates an exemplary network architecture in which or with which
proposed system can be implemented in accordance with an embodiment of the present
disclosure.
[0052] As illustrated, in a network implementation, the system 102 can be
communicatively coupled with a set of sensors 106 through network 104. The set of sensors
106 can include EEG sensor to sense EEG signal of a first user 108. The system 102 can be
implemented using any or a combination of hardware components and software components
such as a server, a computing system, a computing device, a security device and the like, such
that embodiments of the present disclosure can convert EEG signal to speech.
[0053] Further, the system 102 can be communicatively coupled with plurality of
computing devices 110-1, 110-2……110-N (collectively referred to as computing devices
110 and individually referred to as computing device 110 hereinafter) through the network
104.
[0054] Further, the system 102 can interact with plurality of second users 112-1, 112-
2…112-N (collectively referred to as second users 112, and individually referred to as second
user user 112 hereinafter), through the computing devices 110 or through applications
residing on the computing devices 110. In an implementation, the system 102 can be access
by applications residing on any operating system, including but not limited to, AndroidTM,
iOSTM, and the like. Examples of the computing devices 110 can include, but are not limited
to, a portable computer, a personal digital assistant, a handheld device, and a workstation. In
a preferred embodiment, the computing devices 110 are mobile phones of the respective
second users 112.
[0055] The network 104 can be a wireless network, a wired network or a combination
thereof that can be implemented as one of the different types of networks, such as Intranet,
Local Area Network (LAN), Wide Area Network (WAN), Internet, and the like. Further, the
10
network 104 can either be a dedicated network or a shared network. The shared network can
represent an association of the different types of networks that can use variety of protocols,
for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet
Protocol (TCP/IP), Wireless Application Protocol (WAP), and the like.
[0056] In an embodiment, the system 102 can enable registration of the user 112. The
registration can be based on details such as name, address, e-mail address, phone number, and
the like. Also, the system 102 can utilize a unique identifier such as PAN card, Aadhar Card,
voter ID, and the like, provided by the user 108, to verify the authenticity of the user 112.
Also, in an embodiment, said unique identifier can avoid multiplicity of registration of the
same user.
[0057] FIG. 2 illustrates an exemplary module diagram for converting EEG signal to
speech in accordance with an embodiment of the present disclosure.
[0058] In an aspect, the system 102 may comprise one or more processor(s) 202. The
one or more processor(s) 202 may be implemented as one or more microprocessors,
microcomputers, microcontrollers, digital signal processors, central processing units, logic
circuitries, and/or any devices that manipulate data based on operational instructions. Among
other capabilities, the one or more processor(s) 202 are configured to fetch and execute
computer-readable instructions stored in a memory 206 of the system 102. The memory 206
may store one or more computer-readable instructions or routines, which may be fetched and
executed to create or share the data units over a network service. The memory 206 may
comprise any non-transitory storage device including, for example, volatile memory such as
RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0059] The system 102 may also comprise an interface(s) 204. The interface(s) 204
may comprise a variety of interfaces, for example, interfaces for data input and output
devices, referred to as I/O devices, storage devices, and the like. The interface(s) 204 may
facilitate communication of the system 102 with various devices coupled to the system 102
such as the set of sensors 106 and the computing devices 110. The interface(s) 204 may also
provide a communication pathway for one or more components of the system 102. Examples
of such components include, but are not limited to, processing module 208 and data 210.
[0060] The processing module 208 may be implemented as a combination of
hardware and programming (for example, programmable instructions) to implement one or
more functionalities of the processing module 208. In examples described herein, such
combinations of hardware and programming may be implemented in several different ways.
For example, the programming for the processing module 208 may be processor executable
11
instructions stored on a non-transitory machine-readable storage medium and the hardware
for the processing module 208 may comprise a processing resource (for example, one or
more processors), to execute such instructions. In the present examples, the machine-readable
storage medium may store instructions that, when executed by the processing resource,
implement the processing module 208. In such examples, the processing unit 104 may
comprise the machine-readable storage medium storing the instructions and the processing
resource to execute the instructions, or the machine-readable storage medium may be
separate but accessible to processing unit 104 and the processing resource. In other examples,
the processing module 208 may be implemented by electronic circuitry.
[0061] The data 210 may comprise data that is either stored or generated as a result of
functionalities implemented by any of the components of the processing module 208.
[0062] In an exemplary embodiment, the processing module 208 may comprise an
EEG signal receive module 212, an EEG signal processing module 214, an audio signal
processing module 216 and an audio output module 218.
[0063] It would be appreciated that modules being described are only exemplary
modules and any other module or sub-module may be included as part of the system 102.
These modules too may be merged or divided into super-modules or sub-modules as may be
configured.
[0064] In an embodiment, the EEG signal receive module 212 configured to receive
EEG signal sensed by the set of sensors 106. The set of sensors adapted to sense EEG
parameters of the first user 108 and generate the EEG signal based on the sensed EEG
parameters. The EEG parameters include different wave patterns in the brain such as : -
 Delta waves: Delta is the frequency range up to 4 Hz. It tends to be the highest
in amplitude and the slowest waves. It is seen normally in adults in slow wave sleep.
It is also seen normally in babies. It may occur focally with subcortical lesions and in
general distribution with diffuse lesions, metabolic encephalopathy hydrocephalus or
deep midline lesions. It is usually most prominent frontally in adults (e.g. FIRDA -
Frontal Intermittent Rhythmic Delta) and posteriorly in children (e.g. OIRDA -
Occipital Intermittent Rhythmic Delta).
 Theta waves: Theta is the frequency range from 4 Hz to 7 Hz. Theta is seen
normally in young children. It may be seen in drowsiness or arousal in older children
and adults; it can also be seen in meditation. Excess theta for age represents abnormal
activity. It can be seen as a focal disturbance in focal subcortical lesions; it can be
12
seen in generalized distribution in diffuse disorder or metabolic encephalopathy or
deep midline disorders or some instances of hydrocephalus. On the contrary this range
has been associated with reports of relaxed, meditative, and creative states.
 Alpha waves: Alpha is the frequency range from 7 Hz to 14 Hz. Hans Berger
named the first rhythmic EEG activity he saw as the "alpha wave". This was the
"posterior basic rhythm" (also called the "posterior dominant rhythm" or the
"posterior alpha rhythm"), seen in the posterior regions of the head on both sides,
higher in amplitude on the dominant side. It emerges with closing of the eyes and with
relaxation, and attenuates with eye opening or mental exertion. The posterior basic
rhythm is actually slower than 8 Hz in young children (therefore technically in the
theta range).
 Beta waves: Beta is the frequency range from 15 Hz to about 30 Hz. It is seen
usually on both sides in symmetrical distribution and is most evident frontally. Beta
activity is closely linked to motor behaviour and is generally attenuated during active
movements. Low amplitude beta with multiple and varying frequencies is often
associated with active, busy or anxious thinking and active concentration. Rhythmic
beta with a dominant set of frequencies is associated with various pathologies and
drug effects, especially benzodiazepines. It may be absent or reduced in areas of
cortical damage. It is the dominant rhythm in patients who are alert or anxious or who
have their eyes open.
 Gamma waves: Gamma is the frequency range approximately 30–100 Hz.
Gamma rhythms are thought to represent binding of different populations of neurons
together into a network for the purpose of carrying out a certain cognitive or motor
function.
[0065] The set of sensors EEG sensors 106 coverts the brain thoughts (waves) into
EEG signal. Further, the generated EEG signal is received using the EEG receive module
212.
[0066] In an embodiment, the signal processing module 214 can be configured to
process the received EEG signal in raw form. Since the received EEG signal is weak i.e. it
has low signal strength and the received EEG signal can have various noise signals blended
with it. Therefore, the received EEG signals needs to be processed/conditioned to enable easy
extraction of original signal from the blended signal.
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[0067] Since the received EEG signal is weak, therefore the received EEG signal is
first amplified to a pre-defined level. The EEG signal can be amplified using one or more
amplifiers. The amplifiers can include but not limited to: -
 Power Amplifiers: Although not technically a type, power amplifier is a
general term that refers to the amount of power provided by the power supply circuit
or the amount of power delivered to the load. It is usually used in the last output
stages of a circuit. Examples include: audio power amplifiers, servo motor controllers,
push-pull amplifers and RF power amplifiers. Again, we’ll look at the classifications
of power amplifiers specifically in a little bit, since they’re very important.
 Operational Amplifiers (Op-Amps): Another very important type, an op-amp
is an integrated circuit that acts as a voltage amplifier, and has differential input. It has
a positive and negative input, but a single output with very high gain. Originally, opamps
were created using valves.
 Valve (or) Vacuum Tube Amplifiers: An amplifier that uses vacuum tubes to
provide an increased power or voltage output is known as a valve (or) vacuum tube
amplifier. As mentioned above, op-amps were originally of the valve type, but were
replaced by ICs once they got cheaper, in smaller applications at least. In high power
applications, they’re still in use because of their cost effectiveness and output quality.
They are used in radar, military, high power radio and UHF transmitter applications.
 Transistor Amplifiers: A well-known type of amplifier, specially to
engineering students, a transistor amplifier is a multi-configuration high output
amplifier that uses transistors as the working base. These include bipolar junction
transistors (BJTs) and metal oxide semiconductor field-effect transistors (MOSFETs).
 Klystron: A special type of linear beam vacuum tube, used as an amplifier in
high radio frequencies. It is highly precise and used in large scale operations, usually
comes under Microwave amplifiers.
 Instrument Amplifiers: Specially designed amplifiers to amplify sound, voice
or music. Used mainly in musical instrument applications.
 Distributed Amplifiers: Amplifiers that use transmission lines to temporarily
split the input and amplify each segment individually are called distributed amplifiers.
They’re commonly found in oscilloscopes.
[0068] Now, the amplified signal comprises amplified signal blended with various
unwanted signal that’s combined with the desired signal is called noise. In any circuit, noise
14
can come from anywhere; from external systems as well as from the within a circuit itself.
External sources include a number of sources such as power lines, RF transmitters, nearby
conductors, ignition systems, or motors that turn on and off drawing sudden large currents.
Electromagnetic interference (EMI) is the noise caused by current in other, nearby conductors
or cables. Radio frequency interference (RFI) is also a source of external noise caused by
radiating signals from wireless systems. Something called cross talk is also external and is
caused by nearby conductors or cables that are physically close enough to induce current in
the affected cable.
[0069] The causes of noise can be from the circuit itself, an imperfect design or
layout, noise generated by faulty components or loose connections, or switches in related
circuits or in switching power supplies that feed the circuit. Even long leads can cause
induced noise. One way to reduce internal circuit noise by reducing the length of the leads for
I/O (input and output) as much as is practically possible. Providing filters, isolating
transformers, chokes, circuit protection, and low-noise components are other ways to reduce
the unwanted noise. A differential op amp has the best immunity to noise amongst op amps
by design, for instance. The differential op amp has inherent immunity to external noise
because the two input conductors to the differential op amp, if close to each other, experience
the same interference. The noise that gets coupled into the conductors looks like a commonmode
voltage to the op amp, and common-mode voltage is rejected in a differential op amp.
The internal source of noise caused by switching circuits, for example, requires mixed signal
circuits to keep digital portions isolated from the analog portion of the circuit. The constant
clocks and switching 0s and 1s can introduce noise to the analog portion of the signal.
Keeping digital circuits from contaminating analog circuits with noise is a challenge because
shared ground the circuit can be a source of noise on the analog side. Isolation, filtering, and
physical distance are some common methods to reduce noise in the analog portion of a mixed
signal circuit.
[0070] Another source of external noise includes environmental causes, such as
physical vibration and increases in temperature. The internal noise of components is due to
fundamental physical properties and can increase naturally due to high temperatures, and is
called thermal noise. Thermal noise increases with an increase in environmental temperature.
Thermal noise is also known as Johnson noise. Shot noise is another type of inherent noise
fundamental to physical phenomena, which occurs as a result of charge carriers overcoming
potential barriers, mainly due to fluctuations in the electrical current. Fundamental noise like
15
the above is more of a concern in extreme circumstances such as in sensitive electronics at
very high temperatures.
[0071] Now along with EEG signal blended noise signals also gets amplified. Now, to
improve accuracy the amplified signal can be filtered to remove the noise signals. In an
embodiment, a filter can be used to filter/reject/reduce noise signal from the amplified signal.
The filter can include but not limited to Butterworth filter, Chebyshev filter, Bessel filter,
Elliptical filter.
[0072] In an embodiment, the audio signal processing module 216 can be used to
process the filtered signal. The filtered signal can be decoded using MATLAB, wherein the
filtered signal can be compared with one or more pre-defined signals stored in a first
database. Now, based on the comparison the compared signal can be converted to text. Then
we use either google text to speech (GTTS) API. GTTS is a very easy to use tool which
converts the text entered, into audio which can be saved as a mp3 file on Raspberry
Pi/Arduino and the like. In an embodiment, based on comparison of the filtered signal with
pre-defined signal the received EEG signal can be converted to an audio signal. Further,
plurality of converted audio signals can be used to generate a speech of the user.
[0073] In an embodiment, the audio output module 218 can be configured to transmit
the converted audio signal/ speech to an audio output device. The audio output module can
include a speaker for converting the audio signals/speech to corresponding sound.
[0074] In an embodiment, the audio signal can be transmitted to the computing device
110 associated with the second user 112.
[0075] FIG. 3 is a flow diagram illustrating a process for converting EEG signal to
speech in accordance with an embodiment of the present disclosure.
[0076] In an aspect, the proposed method may be described in general context of
computer executable instructions. Generally, computer executable instructions can include
routines, programs, objects, components, data structures, procedures, modules, functions,
etc., that perform particular functions or implement particular abstract data types. The method
can also be practiced in a distributed computing environment where functions are performed
by remote processing devices that are linked through a communications network. In a
distributed computing environment, computer executable instructions may be located in both
local and remote computer storage media, including memory storage devices.
[0077] The order in which the method as described is not intended to be construed as
a limitation, and any number of the described method blocks may be combined in any order
to implement the method or alternate methods. Additionally, individual blocks may be
16
deleted from the method without departing from the spirit and scope of the subject matter
described herein. Furthermore, the method may be implemented in any suitable hardware,
software, firmware, or combination thereof. However, for ease of explanation, in the
embodiments described below, the method may be considered to be implemented in the
above described system.
[0078] In an aspect, the present method elaborates upon a method for converting an
EEG signal to speech that comprises, at step 302 the EEG signal of the first user 106 a
received, wherein the set of sensors 106 adapted to sense the EEG parameters and generate
the EEG signal based on the sensed EEG parameters of the first user 108. Step 304
processing said received EEG signal, wherein said received EEG signal is amplified, and
amplified signal is filtered to remove noise signals. Step 306 converting, by said processor,
filtered signal to an audio signal, wherein said filtered signal is compared with a pre-defined
signal stored in a first database.
[0079] Further, the converted audio signal could be transmitted to the audio unit,
wherein the audio unit comprises a speaker or a speaker of the computing device associated
with the second user 112.
[0080] FIG. 4. illustrates an exemplary computer system in which or with which
embodiments of the present invention can be utilized in accordance with embodiments of the
present disclosure.
[0081] Computer system 400 includes a bus 420 or other communication mechanism
for communicating information, and a processor 470 coupled with bus 420 for processing
information. Computer system 400 can also include a main memory 430 or other nontransitory
computer-readable medium, such as a random-access memory (RAM) or other
dynamic storage device, which can then be coupled to bus 420 for storing information and
instructions to be executed by processor 470. Main memory 430 also may be used for storing
temporary variables or other intermediate information during execution of instructions to be
executed by processor 470. Computer system 400 may further include a read only memory
(ROM) 440 or other static storage device coupled to bus 420 for storing static information
and instructions for processor 470. A data/external storage device 410, such as a magnetic
disk or optical disk, is provided and coupled to bus 420 for storing information and
instructions.
[0082] Computer system 400 may be coupled via bus 420 to a display (not shown),
such as a cathode ray tube (CRT), for displaying information to a user. An input device (not
shown), including alphanumeric and other keys, can be coupled to bus 420 for
17
communicating information and command selections to processor 470. Another type of user
input device can be cursor control, such as a mouse, a trackball, or cursor direction keys for
communicating direction information and command selections to processor 470 and for
controlling cursor movement on display. This input device typically has two degrees of
freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to
specify positions in a plane.
[0083] The invention is related to the use of computer system 400 for creation and
management of BOMs as elaborated above. According to some embodiments of the
invention, such use may be provided by computer system 400 in response to processor 470
executing one or more sequences of one or more instructions contained in the main memory
430. Such instructions may be read into main memory 430 from another computer-readable
medium, such as storage device 450. Execution of the sequences of instructions contained in
main memory 430 causes processor 470 to perform the process steps described herein. One or
more processors in a multi-processing arrangement may also be employed to execute the
sequences of instructions contained in main memory 430. In alternative embodiments, hardwired
circuitry may be used in place of or in combination with software instructions to
implement the invention. Thus, embodiments of the invention are not limited to any specific
combination of hardware circuitry and software.
[0084] The term “computer-readable medium” as used herein refers to any medium
that participates in providing instructions to processor 470 for execution. Such a medium may
take many forms, including but not limited to, non-volatile media, volatile media, and
transmission media. Non-volatile media includes, for example, optical or magnetic disks,
such as storage device 450. Volatile media includes dynamic memory, such as main memory
430. Transmission media includes coaxial cables, copper wire and fiber optics, including the
wires that comprise bus 420. Transmission media can also take the form of acoustic or light
waves, such as those generated during radio wave and infrared data communications.
[0085] Common forms of computer-readable media include, for example, a floppy
disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM,
any other optical medium, punch cards, paper tape, any other physical medium with patterns
of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip or
cartridge, a carrier wave as described hereinafter, or any other medium from which a
computer can read.
[0086] Various forms of computer-readable media may be involved in carrying one or
more sequences of one or more instructions to processor 470 for execution. For example, the
18
instructions may initially be carried on a magnetic disk of a remote computer. The remote
computer can load the instructions into its dynamic memory and send the instructions over a
telephone line using a modem. A modem local to computer system 400 can receive the data
on the telephone line and use an infrared transmitter to convert the data to an infrared signal.
An infrared detector coupled to bus 420 can receive the data carried in the infrared signal and
place the data on bus 420. Bus 420 carries the data to main memory 430, from which
processor 470 retrieves and executes the instructions. The instructions received by main
memory 430 may optionally be stored on storage device 450 either before or after execution
by processor 470.
[0087] Computer system 400 also includes a communication interface 460 coupled to
bus 420. Communication interface 460 can provide a two-way data communication coupling
to a network link (not shown) that can be connected to a local network (not shown). For
example, communication interface 460 may be an integrated services digital network (ISDN)
card or a modem to provide a data communication connection to a corresponding type of
telephone line. As another example, communication interface 460 may be a local area
network (LAN) card to provide a data communication connection to a compatible LAN.
Wireless links may also be implemented. In any such implementation, communication
interface 460 sends and receives electrical, electromagnetic or optical signals that carry data
streams representing various types of information.
[0088] Although the proposed system has been elaborated as above to include all the
main parts, it is completely possible that actual implementations may include only a part of
the proposed modules/engines or a combination of those or a division of those in various
combinations across multiple devices that can be operatively coupled with each other,
including in the cloud. Further the modules/engines can be configured in any sequence to
achieve objectives elaborated. Also, it can be appreciated that proposed system can be
configured in a computing device or across a plurality of computing devices operatively
connected with each other, wherein the computing devices can be any of a computer, a
laptop, a smart phone, an Internet enabled mobile device and the like. All such modifications
and embodiments are completely within the scope of the present disclosure.
[0089] Embodiments of the present disclosure may be implemented entirely
hardware, entirely software (including firmware, resident software, micro-code, etc.) or
combining software and hardware implementation that may all generally be referred to herein
as a “circuit,” “module,” “component,” or “system.” Furthermore, aspects of the present
19
disclosure may take the form of a computer program product comprising one or more
computer readable media having computer readable program code embodied thereon.
[0090] Thus, it will be appreciated by those of ordinary skill in the art that the
diagrams, schematics, illustrations, and the like represent conceptual views or processes
illustrating systems and methods embodying this invention. The functions of the various
elements shown in the figures may be provided through the use of dedicated hardware as well
as hardware capable of executing associated software. Similarly, any switches shown in the
figures are conceptual only. Their function may be carried out through the operation of
program logic, through dedicated logic, through the interaction of program control and
dedicated logic, or even manually, the particular technique being selectable by the entity
implementing this invention. Those of ordinary skill in the art further understand that the
exemplary hardware, software, processes, methods, and/or operating systems described
herein are for illustrative purposes and, thus, are not intended to be limited to any particular
named.
[0091] As used herein, and unless the context dictates otherwise, the term "coupled
to" is intended to include both direct coupling (in which two elements that are coupled to
each other contact each other) and indirect coupling (in which at least one additional element
is located between the two elements). Therefore, the terms "coupled to" and "coupled with"
are used synonymously. Within the context of this document terms "coupled to" and "coupled
with" are also used euphemistically to mean “communicatively coupled with” over a
network, where two or more devices are able to exchange data with each other over the
network, possibly via one or more intermediary device.
[0092] It should be apparent to those skilled in the art that many more modifications
besides those already described are possible without departing from the inventive concepts
herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of
the appended claims. Moreover, in interpreting both the specification and the claims, all
terms should be interpreted in the broadest possible manner consistent with the context. In
particular, the terms “comprises” and “comprising” should be interpreted as referring to
elements, components, or steps in a non-exclusive manner, indicating that the referenced
elements, components, or steps may be present, or utilized, or combined with other elements,
components, or steps that are not expressly referenced. Where the specification claims refers
to at least one of something selected from the group consisting of A, B, C …. and N, the text
should be interpreted as requiring only one element from the group, not A plus N, or B plus
N, etc.
20
[0093] While the foregoing describes various embodiments of the invention, other and
further embodiments of the invention may be devised without departing from the basic scope
thereof. The scope of the invention is determined by the claims that follow. The invention is
not limited to the described embodiments, versions or examples, which are included to enable
people having ordinary skill in the art to make and use the invention when combined with
information and knowledge available to the person having ordinary skill in the art.
ADVANTAGES OF THE PRESENT DISCLOSURE
[0094] The present disclosure provides system and method to convert EEG signal to
speech.
[0095] The present disclosure provides system and method to convert EEG signal to
speech that is cost efficient and easy to implement.
[0096] The present disclosure provides system and method to convert EEG signal to
speech that enables accessing of converted speech remotely.
[0097] The present disclosure provides system and method to convert EEG signal to
speech that enables speech impaired user to communicate with others.

We Claim:
1. A system for converting an EEG signal to speech, said system comprising:
a processor coupled with a memory, the memory storing instructions executable
by the processor to:
receive the EEG signal of a first user;
process said received EEG signal, wherein said received EEG signal is
amplified, and amplified signal is filtered to remove noise signals;
convert filtered signal to an audio signal, wherein said filtered signal is
compared with one or more pre-defined signals stored in a first database, and
wherein each of said one or more pre-defined signals is associated with a
corresponding audio signal, and
wherein based on comparison said filtered signals is converted to said
audio signal.
2. The system as claimed in claim 1, wherein said processor configured to transmit said
converted audio signal to an audio output device.
3. The system as claimed in claim 2, wherein said audio output device is associated with a
computing device associated with a second user.
4. The system as claimed in claim 1, wherein said EEG signal is acquired from one or more
EEG sensors placed at pre-defined position on body of said first user.
5. The system as claimed in claim 1, wherein said filtered signal is converted using a
MATLAB, and wherein said filtered signal is converted to corresponding text and said
converted text is converted to said audio signal.
6. The system as claimed in claim 1, wherein combination of plurality of converted audio
signals forms a speech.
7. A method for converting an EEG signal to speech, said method comprising:
receiving, by a processor, the EEG signal of a first user;
processing, by said processor, said received EEG signal, wherein said received
EEG signal is amplified, and amplified signal is filtered to remove noise signals;
converting, by said processor, filtered signal to an audio signal, wherein said
filtered signal is compared with one or more pre-defined signals stored in a first
database.
8. The method as claimed in claim 7, wherein said method comprises transmitting using
said processor, the converted audio signal to an audio output device.
22
9. The method as claimed in claim 7, wherein said method comprises converting the filtered
signal by said processor using a MATLAB, and wherein said filtered signal is converted
to corresponding text and said converted text is converted to said audio signal.
10. The method as claimed in claim 7, wherein said method comprises combination of
plurality of converted audio signals to form a speech.