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Method And System Of Estimating Clean Speech Parameters From Noisy Speech Parameters

Abstract: A method and system is provided for estimating clean speech parameters from noisy speech parameters. The method is performed by acquiring speech signals, estimating noise from the acquired speech signals, computing speech features from the acquired speech signals, estimating model parameters from the computed speech features and estimating clean parameters from the estimated noise and the estimated model parameters.

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Notices, Deadlines & Correspondence

Patent Information

Application #
Filing Date
15 March 2016
Publication Number
46/2017
Publication Type
INA
Invention Field
ELECTRONICS
Status
Email
iprdel@lakshmisri.com
Parent Application
Patent Number
Legal Status
Grant Date
2023-10-26
Renewal Date

Applicants

TATA CONSULTANCY SERVICES LIMITED
Nirmal Building, 9th Floor, Nariman Point, Mumbai-400021, Maharashtra, India

Inventors

1. PANDA, Ashish
Tata Consultancy Services Limited Desk No. 5G2, Innovation Lab Yantra Park -(STPI), 2nd Pokharan Road, Subash Nagar Unit No. 6 Thane-400601, Maharashtra, India
2. KOPPARAPU, Sunil Kumar
Tata Consultancy Services Limited Desk No. 5G2, Innovation Lab Yantra Park -(STPI), 2nd Pokharan Road, Subash Nagar Unit No. 6 Thane-400601, Maharashtra, India

Specification

Claims:1. A method of estimating clean speech parameters from noisy speech parameters, said method comprising processor implemented steps of:

acquisition of speech signals using a speech acquisition module (202);
estimation of noise from said acquired speech signals using a noise estimation module (204);
computation of speech features from said acquired speech signals using a feature extraction module (206);
estimation of model parameters from the said computed speech features using a parameter estimation module (208);
estimation of clean parameters from said estimated noise and said estimated model parameters using a clean parameter estimation module (210);

2. The method as claimed in claim 1, wherein said speech acquisition module (202) further converts the said acquired speech signals from analog to digital waveforms.

3. The method as claimed in claim 1, wherein said estimation of noise using the noise estimation module is performed during training phase.

4. The method as claimed in claim 1, wherein said estimation of noise can further be performed through non-speech frames of said acquired speech signals.

5. The method as claimed in claim 1, wherein Mel-Frequency Cepstral Coefficients are used as said speech features in the feature extraction module.

6. The method as claimed in claim 1, wherein said estimated noise and said estimated model parameters are first converted into their spectral domain representations.

7. The method as claimed in claim 1, wherein the estimated clean parameters are in their spectral domain representation.

8. The method as claimed in Claim 7, wherein the estimated clean parameters are converted from their spectral domain representation to feature domain representation.

9. A system of estimating clean speech parameters from noisy speech parameters, said system comprising:

a processor;
a data bus coupled to said processor; and
a computer-usable medium embodying computer code, said computer-usable medium being coupled to said data bus, said computer program code comprising instructions executable by said processor and configured for operating
a speech acquisition module (202) adapted for acquiring speech signals;
a noise estimation module (204) adapted for estimating noise from said acquired speech signals;
a feature extraction module (206) adapted for computing speech features from said acquired speech signals;
a parameter estimation module (208) adapted for estimating model parameters from the said computed speech features;
a clean parameter estimation module (210) adapted for estimating clean parameters from said estimated noise and said estimated model parameters.

, Description:As Attached

Documents

Application Documents

# Name Date
1 Form 5 [15-03-2016(online)].pdf 2016-03-15
2 Form 3 [15-03-2016(online)].pdf 2016-03-15
3 Form 18 [15-03-2016(online)].pdf 2016-03-15
4 Drawing [15-03-2016(online)].pdf 2016-03-15
5 Description(Complete) [15-03-2016(online)].pdf 2016-03-15
6 Form 26 [04-07-2016(online)].pdf 2016-07-04
7 201621009058-POWER OF ATTORNEY-(07-07-2016).pdf 2016-07-07
8 201621009058-CORRESPONDENCE-(07-07-2016).pdf 2016-07-07
9 Other Patent Document [31-08-2016(online)].pdf 2016-08-31
10 REQUEST FOR CERTIFIED COPY [06-02-2017(online)].pdf 2017-02-06
11 Form 3 [08-03-2017(online)].pdf 2017-03-08
12 Request For Certified Copy-Online.pdf 2018-08-11
13 Abstract.jpg 2018-08-11
14 201621009058-Form 1-060916.pdf 2018-08-11
15 201621009058-Correspondence-060916.pdf 2018-08-11
16 201621009058-CORRESPONDENCE(IPO)-(CERTIFIED)-(14-2-2017).pdf 2018-08-11
17 201621009058-FER.pdf 2019-08-28
18 201621009058-Information under section 8(2) [11-02-2020(online)].pdf 2020-02-11
19 201621009058-FORM 3 [11-02-2020(online)].pdf 2020-02-11
20 201621009058-OTHERS [25-02-2020(online)].pdf 2020-02-25
21 201621009058-FER_SER_REPLY [25-02-2020(online)].pdf 2020-02-25
22 201621009058-DRAWING [25-02-2020(online)].pdf 2020-02-25
23 201621009058-CLAIMS [25-02-2020(online)].pdf 2020-02-25
24 201621009058-ABSTRACT [25-02-2020(online)].pdf 2020-02-25
25 201621009058-PatentCertificate26-10-2023.pdf 2023-10-26
26 201621009058-IntimationOfGrant26-10-2023.pdf 2023-10-26

Search Strategy

1 2019-08-0512-32-51_27-08-2019.pdf

ERegister / Renewals

3rd: 06 Nov 2023

From 15/03/2018 - To 15/03/2019

4th: 06 Nov 2023

From 15/03/2019 - To 15/03/2020

5th: 06 Nov 2023

From 15/03/2020 - To 15/03/2021

6th: 06 Nov 2023

From 15/03/2021 - To 15/03/2022

7th: 06 Nov 2023

From 15/03/2022 - To 15/03/2023

8th: 06 Nov 2023

From 15/03/2023 - To 15/03/2024

9th: 06 Nov 2023

From 15/03/2024 - To 15/03/2025

10th: 12 Mar 2025

From 15/03/2025 - To 15/03/2026