System for generating language model, method of generating language model, and program for language model generation

• US 20110077943A1
• Filed: 06/18/2007
• Published: 03/31/2011
• Est. Priority Date: 06/26/2006
• Status: Abandoned Application

• Current Assignee: NEC Corporation
• Original Assignee: NEC Corporation
• Inventors: Nagatomo, Kentaro, Miki, Kiyokazu
• Application Number:
  US12/308,400
• Publication Number:
  US 20110077943A1
• Time in Patent Office: Days
• US Class Current: 704/250
• CPC Class Codes: G10L 15/183 using context dependencies, e.g. language models

Abstract

A first system for generating a language model is a system for generating a language model including: a topic history dependent language model storing unit; a topic history accumulation unit; and a language score calculation unit. In the system for generating the language model, a language score corresponding to history of topics is calculated by the language score calculation unit using history of topics in an utterance accumulated in the topic history accumulation unit and a language model stored in the topic history dependent language model storing unit. The topic history dependent language model storing unit may store a topic history dependent language model dependent on only most recent n topics. The topic history accumulation unit may accumulate only most recent n topics.

Claims

1. A system for generating a language model, comprising:

a topic history dependent language model storing unit;

a topic history accumulation unit; and

a language score calculation unit,

wherein a language score corresponding to history of topics is calculated by said language score calculation unit using history of topics in an utterance accumulated in said topic history accumulation unit and a language model stored in said topic history dependent language model storing unit.

2. The system for generating the language model as set forth in claim 1,

wherein said topic history dependent language model storing unit stores a topic history dependent language model dependent on only most recent n topics.

3. The system for generating the language model as set forth in claim 1,

wherein said topic history accumulation unit accumulates only most recent n topics.

4. The system for generating the language model as set forth in claim 1,

wherein said topic history dependent language model storing unit stores a topic-specific language model, and

said language score calculation unit selects a language model from the topic-specific language models according to the topic history accumulated in said topic history accumulation unit and calculates the language score using a new language model generated by combining the selected language models.

5. The system for generating the language model as set forth in claim 4,

wherein said language score calculation unit selects a topic-specific language model corresponding to the topic accumulated in said topic history accumulation unit.

6. The system for generating the language model as set forth in claim 4,

wherein said language score calculation unit linearly couples probability parameters of the selected topic-specific language models.

7. The system for generating the language model as set forth in claim 6,

wherein said language score calculation unit further uses a coefficient which is smaller for an older topic in the topic history in the case of linear coupling.

8. The system for generating the language model as set forth in claim 4,

wherein said topic history dependent language model storing unit stores a topic-specific language model in which a distance can be defined between the language models, and

said language score calculation unit selects a topic-specific language model corresponding to the topic accumulated in said topic history accumulation unit and a different topic-specific language model which is small in distance with said topic-specific language model corresponding to the topic.

9. The system for generating the language model as set forth in claim 8,

wherein said language score calculation unit linearly couples probability parameters of the selected topic-specific language models.

10. The system for generating the language model as set forth in claim 9,

wherein said language score calculation unit further uses a coefficient which is smaller for an older topic in the topic history in the case of linear coupling.

11. The system for generating the language model as set forth in claim 9,

wherein said language score calculation unit further uses a coefficient which is smaller for a topic-specific language model which is farther in distance from the topic-specific language model of the topic appearing in the topic history in the case of linear coupling.

12. A voice recognition system comprising a voice recognition unit which performs voice recognition with reference to a language model generated in the system for generating the language model as set forth in claim 1.

25. A computer readable medium which is for making a computer function as the system for generating the language model as set forth in claim 1.

26. A computer readable medium which is for making a computer function as the voice recognition system as set forth in claim 12.

13. A method of generating a language model in a system for generating a language model which comprises a topic history dependent language model storing unit, a topic history accumulation unit, and a language score calculation unit,

wherein a language score corresponding to history of topics is calculated by said language score calculation unit using history of topics in an utterance accumulated in said topic history accumulation unit and a language model stored in said topic history dependent language model storing unit.

14. The method of generating the language model as set forth in claim 13,

wherein said topic history dependent language model storing unit stores a topic history dependent language model dependent on only most recent n topics.

15. The method of generating the language model as set forth in claim 13,

wherein said topic history accumulation unit accumulates only most recent n topics.

16. The method of generating the language model as set forth in claim 13,

wherein said topic history dependent language model storing unit stores a topic-specific language model, and

said language score calculation unit selects a language model from the topic-specific language models according to the topic history accumulated in said topic history accumulation unit and calculates the language score using a new language model generated by combining the selected language models.

17. The method of generating the language model as set forth in claim 16,

wherein said language score calculation unit selects a topic-specific language model corresponding to the topic accumulated in said topic history accumulation unit.

18. The method of generating the language model as set forth in claim 16,

wherein said language score calculation unit linearly couples probability parameters of the selected topic-specific language models.

19. The method of generating the language model as set forth in claim 18,

wherein said language score calculation unit further uses a coefficient which is smaller for an older topic in the topic history in the case of linear coupling.

20. The method of generating the language model as set forth in claim 16,

wherein said topic history dependent language model storing unit stores a topic-specific language model in which a distance can be defined between the language models, and

said language score calculation unit selects a topic-specific language model corresponding to the topic accumulated in said topic history accumulation unit and a different topic-specific language model which is small in distance with said topic-specific language model corresponding to the topic.

21. The method of generating the language model as set forth in claim 20,

wherein said language score calculation unit linearly couples probability parameters of the selected topic-specific language models.

22. The method of generating the language model as set forth in claim 21,

wherein said language score calculation unit further uses a coefficient which is smaller for an older topic in the topic history in the case of linear coupling.

23. The method of generating the language model as set forth in claim 21,

wherein said language score calculation unit further uses a coefficient which is smaller for a topic-specific language model which is farther in distance from the topic-specific language model of the topic appearing in the topic history in the case of linear coupling.

24. A voice recognition method comprising a voice recognition unit which performs voice recognition with reference to a language model generated in the method of generating the language model as set forth in claim 13.