SPEAKER ADAPTATION METHOD AND APPARATUS

• US 20120109646A1
• Filed: 09/02/2011
• Published: 05/03/2012
• Est. Priority Date: 11/02/2010
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: BAK, Eun-Sang
• Application Number:
  US13/224,489
• Publication Number:
  US 20120109646A1
• Time in Patent Office: Days
• US Class Current: 704/229
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/065 Adaptation

Abstract

A speaker adaptation method and apparatus are provided including extracting adapted data from speech recognition data stored in a database, and modifying a sound model by using a speaker adaptation method selected based on a type of the extracted adapted data.

Claims

1. A speaker adaptation method comprising:

extracting adapted data from speech recognition data stored in a database, wherein the stored speech recognition data comprises a first type of data and a second type of data;

selecting a speaker adaptation method according to whether the extracted data comprises the first type of data or the second type of data; and

modifying a sound model by using the selected speaker adaptation method.

2. The speaker adaptation method of claim 1, further comprising storing the speech recognition data in the database,

wherein the speech recognition data comprises input speech data on which speech recognition has been performed using a sound model.

3. The speaker adaptation method of claim 2, wherein

the first type of data comprises speech recognition data for which the speech recognition was correctly performed and the second type of data comprises speech recognition data for which the speech recognition was not correctly performed, and

the storing of the speech recognition data comprises sorting the speech recognition data into the first type of data and the second type of data.

4. The speaker adaptation method of claim 3, wherein the first type of data comprises text data generated by recognizing the input speech data, in addition to the input speech data.

5. The speaker adaptation method of claim 3, wherein the second type of data comprises text data generated when an error in text data generated by recognizing the input speech data was corrected, in addition to the input speech data.

6. The speaker adaptation method of claim 3, wherein the extracting of the adapted data comprises, extracting the second type of data in an order beginning with speech recognition data containing most words with a highest error occurrence.

7. The speaker adaptation method of claim 3, wherein the extracting of the adapted data comprises extracting the adapted data in an order beginning with speech recognition data containing speech data with a lowest pattern similarity to a pattern of the sound model.

8. The speaker adaptation method of claim 3, wherein the extracting of the adapted data comprises extracting the adapted data in an order beginning with speech recognition data containing speech data containing most words that are most frequently used.

9. The speaker adaptation method of claim 3, wherein, when the adapted data comprises the first type of data, the modifying the sound model comprises using a global adaptation method using the extracted adapted data.

10. The speaker adaptation method of claim 9, wherein the global adaptation method is a maximum likelihood linear regression method.

11. The speaker adaptation method of claim 3, wherein, when the adapted data comprises the second data, modifying the sound model comprises using a local adaptation method using the extracted adapted data.

12. The speaker adaptation method of claim 11, wherein the local adaptation method comprises a maximum a posteriori method.

13. A speaker adaptation apparatus comprising:

a database in which speech recognition data is stored, wherein the speech recognition data comprises a first type of data and a second type of data;

an adapted data extracting unit which extracts adapted data from speech recognition data stored in the database; and

a speaker adaptation unit which modifies a sound model by using a speaker adaptation method based on whether the extracted data comprises the first type of data or the second type of data.

14. The speaker adaptation apparatus of claim 13, wherein the speech recognition data comprises input speech data on which speech recognition has been performed using a sound model.

15. The speaker adaptation apparatus of claim 14, wherein

the first type of data comprises speech recognition data for which the speech recognition was correctly performed and the second type of data comprises speech recognition data for which the speech recognition was not correctly performed.

16. The speaker adaptation apparatus of claim 15, wherein the first type of data comprises text data generated by recognizing the input speech data, in addition to the input speech data.

17. The speaker adaptation apparatus of claim 15, wherein the second type of data comprises text data generated when an error in text data generated by recognizing the input speech data was corrected, in addition to the input speech data.

18. The speaker adaptation apparatus of claim 15, wherein, when the extracted adapted data is the second type of data, the adapted data extracting unit extracts the adapted data in an order beginning with speech recognition data containing most words with a highest error occurrence.

19. The speaker adaptation apparatus of claim 15, wherein the adapted data extracting unit extracts the adapted data in an order beginning with speech recognition data containing speech data with a lowest pattern similarity to a pattern of the sound model.

20. The speaker adaptation apparatus of claim 15, wherein the adapted data extracting unit extracts the adapted data in an order beginning with speech recognition data containing speech data containing most words that are most frequently used.

21. The speaker adaptation apparatus of claim 15, wherein, when the extracted adapted data comprises the first type of data, the speaker adaptation unit modifies the sound model by using a global adaptation method using the extracted adapted data.

22. The speaker adaptation apparatus of claim 21, wherein the global adaptation method is a maximum likelihood linear regression method.

23. The speaker adaptation apparatus of claim 15, wherein, when the extracted adapted data is the second type of data, the speaker adaptation unit modifies the sound model by using a local adaptation method using the extracted adapted data.

24. The speaker adaptation apparatus of claim 23, wherein the local adaptation method comprises a maximum a posteriori method.

25. A non-transitory computer readable recording medium having recorded thereon a program for executing a method comprising:

extracting adapted data from speech recognition data stored in a database, wherein the stored speech recognition data comprises a first type of data and a second type of data;

selecting a speaker adaptation method according to whether the extracted data comprises the first type of data or the second type of data; and

modifying a sound model by using the selected speaker adaptation method.

26. A speaker adaptation method comprising:

extracting speech recognition data from a database, wherein the speech recognition data comprises one of a first type of data and a second type of data, wherein the first type of data comprises input speech data and data generated by correctly recognizing the input speech data, and the second type of data comprises input speech data and data generated when an error in text data generated by incorrectly recognizing the input speech data is corrected;

selecting a first speaker adaptation method when the extracted speech recognition data comprises the first type of data, and selecting a second speaker adaptation method, different from the first speaker adaptation method, when the extracted speech recognition data comprises the second type of data; and

modifying a sound model using the selected speaker adaptation method.