Hands-free voice dialing for portable and remote devices

• US 20060009974A1
• Filed: 07/09/2004
• Published: 01/12/2006
• Est. Priority Date: 07/09/2004
• Status: Abandoned Application

• Current Assignee: Panasonic Corporation (Panasonic Holdings Corporation)
• Original Assignee: Matsushita Electric Industrial Company Limited (Panasonic Holdings Corporation)
• Inventors: Rigazio, Luca, Junqua, Jean-Claude, Lei, Jia
• Application Number:
  US10/888,916
• Publication Number:
  US 20060009974A1
• Time in Patent Office: Days
• US Class Current: 704/257
• CPC Class Codes: G10L 15/083 Recognition networks G10L15/142, G10L15/16 take precedence
• CPC Class Codes: G10L 2015/227 of the speaker; Human-factor methodology
• CPC Class Codes: G10L 2015/228 of application context
• CPC Class Codes: H04M 1/271 controlled by voice recognition
• CPC Class Codes: H04M 2250/60 logging of communication history, e.g. outgoing or incoming calls, missed calls, messages or URLs

Abstract

Dynamically constructed grammar-constraints and frequency or statistics-based constraints are used to constrain the speech recognizer and to optionally rescore the output to improve recognition accuracy. The recognition system is well adapted for hands-free operation of portable devices, such as for voice dialing operations.

Claims

1. An improved speech recognition system comprising:

an automatic speech recognizer that implements at least one constrainable search algorithm;

a dynamic constraint builder associated with a user device and configured to construct constraint data learned through observing operation of said user device;

said automatic speech recognizer being configured to access said constraint data and to constrain said search algorithm.

2. The system of claim 1 wherein said recognizer is configured to provide at least one recognition hypothesis and wherein said automatic speech recognizer is configured for communication with said user device and operable to provide said at least one recognition hypothesis to said user device.

3. The system of claim 1 wherein said constrainable search algorithm is a dynamic programming algorithm.

4. The system of claim 1 wherein said recognizer employs a decoding lattice having a forward pass and a backward pass and wherein said constraint data is used to constrain at lease one of said passes.

5. The system of claim 1 wherein said user device is a portable device.

6. The system of claim 1 wherein said user device is a cellular telephone.

7. The system of claim 1 wherein said user device is a telephone and wherein said dynamic constraint builder observes user operation of said telephone in dialing phone numbers.

8. The system of claim 1 wherein said user device is a telephone and wherein said dynamic constraint builder observes said telephone in receiving incoming calls.

9. The system of claim 8 wherein said dynamic constraint builder obtains caller ID codes from said incoming calls.

10. The system of claim 1 wherein said user device has an associated phonebook and wherein said dynamic constraint builder obtains data from said phonebook.

11. The system of claim 1 wherein said automatic speech recognizer is implemented on a system detached from said user device.

12. The system of claim 1 wherein said user device is a telephone and wherein said dynamic constraint builder gathers statistical data reflecting phone numbers called using said telephone.

13. The system of claim 12 wherein said statistical data reflect the frequency of numbers called.

14. The system of claim 12 wherein said statistical data reflect the frequency of area codes accessed.

15. The system of claim 1 wherein said user device is a telephone and wherein said dynamic constraint builder gathers statistical data reflecting the geographical position of said user device during its use.

16. The system of claim 1 wherein said recognizer outputs an N-best hypothesis.

17. The system of claim 16 wherein said constraint data are used to rescore said N-best hypothesis.

18. The system of claim 16 further comprising system for applying a confidence measure to selectively present said N-best hypothesis to the user.

19. The system of claim 18 wherein said user device includes a visual display and wherein said selective presentation of said N-best hypothesis is made to the user on said visual display.

20. The system of claim 18 wherein said user device includes an audible output and wherein said selective presentation of said N-best hypothesis is made to the user through synthesized speech over said audible output.

21. The system of claim 1 further comprising user modification interface cooperating with said dynamic constraint builder and adapted to selectively alter said constraint data in response to user manipulation.

22. The system of claim 1 wherein said user device is a telephone having a call history storage mechanism and wherein said dynamic constraint builder uses said call history storage mechanism to construct constraint data.

23. An improved speech recognition system comprising:

a first recognizer operating under a first set of constraints;

a second recognizer operating under a second set of constraints that differ from said first set;

a decision mechanism to select at least one most probable output candidate from at least one of said first and second recognizers.

24. The system of claim 23 wherein said first recognizer is a tightly constrained recognizer.

25. The system of claim 23 wherein said first set of constraints is derived from a call history log.

26. The system of claim 23 wherein said first set of constraints is derived from a digitally stored phone book.

27. The system of claim 23 wherein said second recognizer is a loosely constrained recognizer.

28. The system of claim 23 wherein said second set of constraints is derived from a predefined phone number grammar.

29. The system of claim 23 wherein said second set of constraints is derived from statistical information gathered during use of a telephone system.

30. The system of claim 23 wherein said decision mechanism employs an empirical criterion.

31. The system of claim 23 wherein said recognizers output confidence scores associated with output candidates and wherein said decision mechanism uses said confidence scores.

32. The system of claim 23 wherein said first and second recognizers are configured to operate in parallel.

33. The system of claim 23 wherein said first and second recognizers are configured to operate in series.