METHOD FOR NON-INTRUSIVE ACOUSTIC PARAMETER ESTIMATION

• US 20150073780A1
• Filed: 12/23/2013
• Published: 03/12/2015
• Est. Priority Date: 09/06/2013
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Inventors: SHARMA, DUSHYANT, NAYLOR, PATRICK, PARADA, PABLO PESO
• Granted Patent: US 9,685,173 B2
• Time in Patent Office: Days
• US Class Current: 704/205
• CPC Class Codes: G10L 25/12 the extracted parameters being prediction coefficients
• CPC Class Codes: G10L 25/60 for measuring the quality of voice signals

Abstract

A system and method for non-intrusive acoustic parameter estimation is included. The method may include receiving, at a computing device, a first speech signal associated with a particular user. The method may include extracting one or more short-term features from the first speech signal. The method may also include determining one or more statistics of each of the one or more short-term features from the first speech signal. The method may further include classifying the one or more statistics as belonging to one or more acoustic parameter classes.

Claims

1. A computer-implemented method for non-intrusive acoustic parameter estimation comprising:

receiving, at a computing device, a first speech signal associated with a user;

extracting one or more short-term features from the first speech signal;

determining one or more statistics of each of the one or more short-term features from the first speech signal; and

classifying the one or more statistics as belonging to one or more acoustic parameter classes.

2. The method of claim 1, wherein the one or more short term features includes a line spectral frequency feature.

3. The method of claim 2, wherein the line spectral frequency feature is based upon, at least in part, a linear predictive coding coefficient.

4. The method of claim 1, wherein the one or more short term features includes at least one of a mel-frequency cepstral coefficient feature, a velocity feature and an acceleration feature.

5. The method of claim 1, wherein the one or more acoustic parameter classes includes a room acoustic parameter class.

6. The method of claim 4 wherein the at least one of a velocity feature and the acceleration feature is computed using a fast fourier transform.

7. The method of claim 1, further comprising:

extracting one or more long-term features from the first speech signal.

8. The method of claim 7, wherein the one or more long-term features includes a feature based upon, at least in part, a Hilbert phase calculation.

9. A non-transitory computer-readable storage medium having stored thereon instructions for non-intrusive acoustic parameter estimation, which when executed by a processor result in one or more operations, the operations comprising:

receiving, at a computing device, a first speech signal associated with a user;

extracting one or more short-term features from the first speech signal;

determining one or more statistics of each of the one or more short-term features from the first speech signal; and

classifying the one or more statistics as belonging to one or more acoustic parameter classes.

10. The non-transitory computer-readable storage medium of claim 9, wherein the one or more short term features includes a line spectral frequency feature.

11. The non-transitory computer-readable storage medium of claim 10, wherein the line spectral frequency feature is based upon, at least in part, a linear predictive coding coefficient.

12. The non-transitory computer-readable storage medium of claim 9, wherein the one or more short term features includes at least one of a mel-frequency cepstral coefficient feature, a velocity feature and an acceleration feature.

13. The non-transitory computer-readable storage medium of claim 9, wherein the one or more acoustic parameter classes includes a room acoustic parameter class.

14. The non-transitory computer-readable storage medium of claim 12 wherein the at least one of a velocity feature and the acceleration feature is computed using a fast fourier transform.

15. The non-transitory computer-readable storage medium of claim 9, further comprising:

extracting one or more long-term features from the first speech signal.

16. The non-transitory computer-readable storage medium of claim 15, wherein the one or more long-term features includes a feature based upon, at least in part, a Hilbert phase calculation.

17. A system for non-intrusive acoustic parameter estimation comprising:

one or more processors configured to receive a first speech signal associated with a particular user, the one or more processors further configured to extract one or more short-term features from the first speech signal, the one or more processors further configured to determine one or more statistics of each of the one or more short-term features from the first speech signal, the one or more processors further configured to classify the one or more statistics as belonging to one or more acoustic parameter classes.

18. The system of claim 17, wherein the one or more short term features includes a line spectral frequency feature.

19. The system of claim 17, wherein the one or more acoustic parameter classes includes a room acoustic parameter class.

20. The system of claim 17, wherein the one or more processors are further configured to extract one or more long-term features from the first speech signal, the one or more long-term features including a feature based upon, at least in part, a Hilbert phase calculation.