SPEECH RECOGNITION METHOD AND SYSTEM WITH INTELLIGENT SPEAKER IDENTIFICATION AND ADAPTATION

• US 20080147396A1
• Filed: 07/03/2007
• Published: 06/19/2008
• Est. Priority Date: 12/13/2006
• Status: Abandoned Application

• Current Assignee: Delta Electronics Incorporated
• Original Assignee: Delta Electronics Incorporated
• Inventors: Wang, Jui-Chang
• Application Number:
  US11/772,877
• Publication Number:
  US 20080147396A1
• Time in Patent Office: Days
• US Class Current: 704/246
• CPC Class Codes: G10L 15/07 to the speaker
• CPC Class Codes: G10L 15/183 using context dependencies, e.g. language models
• CPC Class Codes: G10L 17/00 Speaker identification or verification techniques

Abstract

A speech recognition method is provided. The speech recognition method includes the steps of (a) receiving a speech from a user; (b) recognizing the speech to generate a recognition result with a score; and (c) according to the score of the recognition result, performing one of the following steps, (c1) preventing from performing an adaptation for an acoustic model but using a utility rate of the speech to learn a new language and grammar probability model when the score is relatively high, (c2) performing a confirmation by the user when the score is relatively low, further comprising: (c21) when the recognition result is confirmed in the confirmation by the user, performing the adaptation in the acoustic model to increase an occurrence probability of the speech and using the utility rate of the speech to learn the new language and grammar probability model, (c22) when the recognition result is rejected in the confirmation by the user, performing the adaptation in the acoustic model to decrease the occurrence probability of the speech.

Claims

1. A speech recognition method, comprising the steps of:

(a) receiving a speech from a user;

(b) recognizing the speech to generate a recognition result with a score; and

(c) according to the score of the recognition result, performing one of the following steps,

(c1) preventing from performing an adaptation for an acoustic model but using a utility rate of the speech to learn a new language and grammar probability model when the score is relatively high,

(c2) performing a confirmation by the user when the score is relatively low, further comprising;

(c21) when the recognition result is confirmed in the confirmation by the user, performing the adaptation in the acoustic model to increase an occurrence probability of the speech and using the utility rate of the speech to learn the new language and grammar probability model,

(c22) when the recognition result is rejected in the confirmation by the user, performing the adaptation in the acoustic model to decrease the occurrence probability of the speech.

2. A method as claimed in claim 1, wherein the speech is an oral command.

3. A speech recognition method for recognizing a respective speech of a plurality of users, in a speech recognition system having a plurality of speech recognition subsystems respectively, comprising:

(a) receiving the speech from a specific user;

(b) recognizing the speech to generate a recognition result with a score;

(c) when the score is relatively high, switching automatically from a first one of the speech recognition subsystems to a specific one of the speech recognition subsystems for the specific user;

(d) when the score is relatively low and in a normal conditions recognizing the speech of the specific user continuously until an enough confidence is accumulated for being switched to the system for the specific user; and

(e) when the score is relatively low and in a special condition, asking the specific user directly for immediately switching to the system for the specific user.

4. A method as claimed in claim 3, wherein each of the users has his own system for recording respective related success and error records for a respective oral command of each of the users and for training and adapting a respective acoustic model and language probability for each of the users.

5. A method as claimed in claim 3, wherein the speech is an oral command.

6. A method as claimed in claim 5, wherein the special condition is that a successive error is occurring for recognizing the oral command.

7. A method as claimed in claim 3, wherein the special condition is that a private data of the specific user is processed.

8. A speech processing method, comprising:

(a) receiving a speech from a user;

(b) recognizing the speech to generate a recognition result;

(c) when errors are successively occurred in the recognition result, detecting the recognition result for getting an error pattern therefor; and

(d) performing an adaptation according to the error pattern.

9. A method as claimed in claim 8, wherein the speech is an oral command.

10. A method as claimed in claim 8, wherein the error pattern comprises:

(a) a first pattern where a successive oral command is recognized identically and rejected repeatedly;

(b) a second pattern where a successive oral command is recognized differently but rejected repeatedly;

(c) a third pattern where a successive voice input is recognized as meaningful speech commands but rejected, the voice input has low energy and is a non-oral voice input with background noises; and

(d) a fourth pattern where the errors are successively odd input errors.

11. A method as claimed in claim 8, wherein the adaptation comprises an inhibition of an error option repeatedly occurring in order to proceed a temporary adaptation of a language and grammar probability model for the user.

12. A method as claimed in claim 8, wherein the adaptation comprises additionally establishing a temporary database for inhibitive commands for decreasing an occurrence probability of an error option successively rejected by the user.

13. A speech recognition/processing system, the system comprising:

a speech recognition unit for receiving and recognizing the speech from a user to generate a recognition result;

an error detecting unit connected with the speech recognition unit for detecting the recognition result to get an error pattern thereof when successive errors for the recognition result continuously occur; and

an error inhibiting unit connected with the error detecting unit for performing an adaptation according to the error pattern.

14. A system as claimed in claim 13, wherein the speech is an oral command.

15. A system as claimed in claim 13, wherein the error pattern comprises:

(a) a first pattern where a successive oral command is recognized identically and rejected repeatedly;

(b) a second pattern where a successive oral command is recognized differently but rejected repeatedly;

(c) a third pattern where a successive voice input is recognized as meaningful speech commands but rejected, the voice input has low energy and is a non-oral voice input with background noises; and

(d) a fourth pattern where the errors are successively odd input errors.

16. A system as claimed in claim 13, wherein the adaptation comprises an inhibition of an error option repeatedly occurring in order to proceed a temporary adaptation of a language and grammar probability model for the user.

17. A system as claimed in claim 13, wherein the adaptation comprises additionally establishing a temporary database for inhibitive commands for decreasing an occurrence probability of an error option successively rejected by the user.