Acoustic confidence driven front-end preprocessing for speech recognition in adverse environments

• US 20040064315A1
• Filed: 09/30/2002
• Published: 04/01/2004
• Est. Priority Date: 09/30/2002
• Status: Abandoned Application

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Sharma, Sangita, Deisher, Michael E.
• Application Number:
  US10/262,297
• Publication Number:
  US 20040064315A1
• Time in Patent Office: Days
• US Class Current: 704/233
• CPC Class Codes: G10L 15/20 Speech recognition techniques specially adapted for robustness in adverse environments, e.g. in noise, of stress induced speech G10L21/02 takes precedence
• CPC Class Codes: G10L 21/0208 Noise filtering

Abstract

A speech processing method that improves overall speech recognition accuracy uses a digital speech signal pre-processing to reduce noise using a noise mitigation algorithm having defined parameters. The digital speech signal is analyzed with a ASR decoder that provides decoder scores; acoustic-unit confidence is determined given the ASR decoder scores; and the noise mitigation algorithm is modified based on the computed acoustic unit confidence.

Claims

1. A speech processing method comprising:

pre-processing a digital speech signal to reduce noise using a noise mitigation algorithm having defined parameters;

analyzing the digital speech signal with a automatic speech recognition system decoder that provides decoder scores;

determining acoustic-unit confidence given the ASR decoder scores; and

modifying at least one of the noise mitigation algorithm and defined parameters based on the computed acoustic unit confidence.

2. The method of claim 1, wherein the noise mitigation algorithm is changed.

3. The method of claim 1, wherein the defined parameters utilized by the noise mitigation algorithm are changed.

4. The method of claim 3, wherein the defined parameters utilized by the noise mitigation algorithm are adaptively modified.

5. The method of claim 3, wherein the defined parameters utilized by the noise mitigation algorithm are adjusted between sets of pre-defined parameters.

6. The method of claim 1, wherein the ASR decoder is a Viterbi decoder, with the first decoding pass recognizing speech and the second pass obtaining acoustic unit scores used for determining acoustic-unit confidence.

7. The method of claim 1, wherein the ASR decoder further uses an acoustic sampling block.

8. The method of claim 7, wherein the acoustic sampling block selects a subset of acoustic-units.

9. The method of claim 8, wherein the subset of acoustic-units comprises calculation of scores for a correct triphone and a subset of the competing triphones.

10. The method of claim 7, wherein the a subset of the speech model parameters are provided to the ASR decoder in the second decoding step.

11. An article comprising a storage medium having stored thereon instructions that when executed by a machine result in:

pre-processing a digital speech signal to reduce noise using a noise mitigation algorithm having defined parameters;

analyzing the digital speech signal with an ASR decoder that provides decoder scores;

determining acoustic-unit confidence given the ASR decoder scores; and

modifying at least one of the noise mitigation algorithm and defined parameters based on the computed unit confidence.

12. The article comprising a storage medium having stored thereon instructions according to claim 11, wherein the noise mitigation algorithm is changed.

13. The article comprising a storage medium having stored thereon instructions according to claim 11, wherein the defined parameters utilized by the noise mitigation algorithm are changed.

14. The article comprising a storage medium having stored thereon instructions according to claim 11, wherein the defined parameters utilized by the noise mitigation algorithm are adaptively modified.

15. The article comprising a storage medium having stored thereon instructions according to claim 11, wherein the defined parameters utilized by the noise mitigation algorithm are adjusted between sets of pre-defined parameters.

16. The article comprising a storage medium having stored thereon instructions according to claim 11, wherein the Viterbi decoder is a two pass decoder, with the first pass recognizing speech and the second pass obtaining acoustic unit scores used for determining acoustic-unit confidence.

17. The article comprising a storage medium having stored thereon instructions according to claim 11, wherein the ASR decoder further uses an acoustic sampling block.

18. The article comprising a storage medium having stored thereon instructions according to claim 17, wherein the acoustic sampling block selects a subset of acoustic-units.

19. The article comprising a storage medium having stored thereon instructions according to claim 18, wherein the subset of acoustic-units comprises calculation of scores for a correct triphone and a subset of the competing triphones.

20. The article comprising a storage medium having stored thereon instructions according to claim 17, wherein the a subset of the speech model parameters are provided to the ASR decoder in the second decoding step.

21. A speech processing system comprising:

a digital speech signal preprocessor to reduce noise using a noise mitigation algorithm having defined parameters that can be modified based on computed acoustic unit confidence;

an ASR decoder that analyzes the digital speech signal after digital speech signal pre-processing and provides decoder scores; and

a post processing module connected to the ASR decoder and the digital speech signal preprocessor to determine acoustic-unit confidence given the ASR decoder scores.

22. The system of claim 21, wherein the noise mitigation algorithm of the digital speech signal preprocessor is changed.

23. The system of claim 21, wherein the defined parameters utilized by the noise mitigation algorithm are changed.

24. The system of claim 21, wherein the defined parameters utilized by the noise mitigation algorithm are adaptively modified.

25. The system of claim 21, wherein the defined parameters utilized by the noise mitigation algorithm are adjusted between sets of pre-defined parameters.

26. The system of claim 21, wherein the ASR decoder is a Viterbi decoder, with the first decoding step recognizing speech and the second decoding step obtaining acoustic unit scores used for determining acoustic-unit confidence.

27. The system of claim 21, wherein the ASR decoder further uses an acoustic sampling block.

28. The system of claim 27, wherein the acoustic sampling block selects a subset of acoustic-units.

29. The system of claim 28, wherein the subset of acoustic-units comprises calculation of scores for a correct triphone and a subset of the competing triphones.

30. The system of claim 27, wherein a subset of the speech model parameters are provided to the ASR decoder in the second decoding step.