Speech recognition

• US 5,903,864 A
• Filed: 11/13/1995
• Issued: 05/11/1999
• Est. Priority Date: 08/30/1995
• Status: Expired due to Term

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: Dragon Systems, Inc. (Microsoft Corporation)
• Inventors: Van Even, Stijn A., Gadbois, Gregory J.
• Primary Examiner(s): Hudspeth, David R.
• Assistant Examiner(s): Storm, Donald L.
• Application Number:
  US08/559,190
• Time in Patent Office: 1,275 Days
• Field of Search: 395/2.66, 395/2.61, 395/2.52, 395/2.09, 395/2.47, 395/2.6, 395/2.4, 395/2.42, 395/2.48, 395/2.53, 395/2.54, 395/2.56, 395/2.58, 395/2.59, 395/2.64 , 395/2.84, 704/253, 704/9, 704/270
• US Class Current: 704/251
• CPC Class Codes: G10L 15/1815 Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
• CPC Class Codes: G10L 2015/085 Methods for reducing search complexity, pruning

Abstract

A method of speech recognition includes recognizing a first utterance, recognizing a second utterance having information that is related to the first utterance, and determining the most probable first and second utterances based on stored information about valid relationships between possible first and second utterances. The most probable second utterance contains information that is semantically related to the most probable first utterance. The recognized first utterance may be recognized continuously and the recognized second utterance may be recognized discretely. The determination of the most probable utterances may include creating a list of possible utterances that could be confused with a recognized utterance and rerecognition of a list of possible utterances against an utterance.

Claims

1. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances, wherein the most probable second utterance and the most probable first utterance are redundant representations expressing the same meaning.

2. The method of claim 1 further including determining validity of one of the recognized first and second utterances, including an invalid recognized utterance in a list of possible utterances, and comparing the invalid recognized utterance with other possible utterances in said list.

3. The method of claim 1 wherein determining the most probable first and second utterances includes rerecognition of one of said spoken utterances against a list of possible utterances.

4. The method of claim 3 further including ranking said list of possible utterances based upon how closely each of the possible utterances corresponds to said one of said spoken utterances.

5. The method of claim 1 further including creating a list of hypothesized possible utterances that relate to at least one of said recognized utterances based on said stored data.

6. The method of claim 5 further including creating and ranking a list of possible utterances based upon how closely each of the possible utterances corresponds to one of said spoken utterances and comparing said ranked list of possible utterances to said list of hypothesized possible utterances for commonality between said lists.

7. The method of claim 1 further including creating a list of possible utterances that could be confused with at least one of said recognized utterances.

8. The method of claim 1 wherein said recognized first utterance is recognized continuously.

9. The method of claim 8 further including creating a list of possible first utterances that may be confused with said recognized first utterance.

10. The method of claim 9 further including creating a list of hypothesized possible second utterances that relate to said possible first utterances in said list of possible first utterances based on said stored data.

11. The method of claim 10 further including adding said recognized second utterance to said list of hypothesized possible second utterances to create a merged list of possible second utterances.

12. The method of claim 11 further including rerecognizing said merged list of possible second utterances against said second spoken utterance to get a ranked list of possible second utterances, said ranking based upon how closely each possible second utterance in said merged list corresponds to said second spoken utterance.

13. The method of claim 12 further including comparing said ranked list of possible second utterances to said list of hypothesized possible second utterances for commonality between said lists, a highest ranked possible second utterance in said ranked list being compared first.

14. The method of claim 13 further including creating a list of hypothesized possible first utterances from said ranked list of possible second utterances based on said stored data.

15. The method of claim 14 further including adding said recognized first utterance to said hypothesized list of possible first utterances to create a merged list of possible first utterances.

16. The method of claim 15 further including rerecognizing said merged list of possible first utterances against said first spoken utterance to get a ranked list of possible first utterances having a ranking based upon how closely each possible first utterance in said merged list of possible first utterances corresponds to said first spoken utterance.

17. The method of claim 16 further including evaluating a possible first utterance ranked second in said ranked list of possible first utterances by determining whether a distance parameter associated with said second ranked possible first utterance is within an acceptable limit.

18. The method of claim 17 further including indicating to a user when said second ranked possible first utterance is not within said acceptable limit and no commonality exists between said ranked list of possible second utterances and said list of hypothesized possible second utterances.

19. The method of claim 1 wherein said recognized second utterance is recognized discretely.

20. The method of claim 1 wherein said first spoken utterance comprises a zipstate and said second spoken utterance comprises a city from a destination address on a package, said determination of the most probable first and second utterances resulting in the sorting of said package according to the package'"'"'s destination address.

21. The method of claim 1 wherein said first spoken utterance comprises a word and said second spoken utterance comprises spelled prefix including ordered symbols.

22. The method of claim 21 further including creating a list of possible prefixes that could be confused with said recognized second utterance.

23. The method of claim 22 wherein said recognized second utterance comprises at least one symbol and creating said list of possible prefixes includes determining, in the context of a preceding symbol or silence, a probability of confusing each symbol in said recognized second utterance with each symbol in a list of possible symbols.

24. The method of claim 22 wherein said recognized second utterance comprises at least one symbol and creating said list of possible prefixes includes determining, in the context of a preceding symbol or silence, a probability of confusing each symbol in said recognized second utterance with more than one symbol.

25. The method of claim 22 wherein said recognized second utterance comprises at least one symbol and creating said list of possible prefixes includes determining, in the context of a preceding symbol or silence, a probability of confusing each symbol in said recognized second utterance with an absence of a symbol.

26. The method of claim 22 wherein creating said list of possible prefixes includes replacing a sequence of symbols with a single symbol.

27. The method of claim 21 wherein said first spoken utterance comprises a spelled word and said determination of the most probable first and second utterances results in recognizing said spelled word.

28. A method of generating a choice list from a continuously recognized utterance comprising:

recognizing a spoken utterance comprising a series of symbols to identify a recognized utterance corresponding to the spoken utterance,

consulting stored information including confusion values for each symbol in the series of symbols to determine the probability of confusing possible utterances with said recognized utterance, said confusion values representing the probability of confusing each symbol in the series of symbols with each symbol in a list of possible symbols, symbols from said list of possible symbols being combined to form each possible utterance of said possible utterances, and

producing a list of possible utterances from the stored information that could be confused with the recognized utterance.

29. The method of claim 28 further including rerecognizing said spoken utterance against a merged list of said list of possible utterances and said recognized utterance to create a ranked list of possible utterances having a ranking based upon how closely each utterance in said merged list corresponds to said spoken utterance.

30. The method of claim 28 wherein said spoken utterance is recognized continuously.

31. A method of recognizing ambiguous inputs including:

recognizing a first ambiguous input to identify a recognized first input corresponding to the first ambiguous input,

recognizing a second ambiguous input having information that is related to said first ambiguous input to identify a recognized second input corresponding to the second ambiguous input, and

determining most probable first and second ambiguous inputs based on the recognized first and second inputs and on stored data about valid relationships between possible first and second ambiguous inputs, wherein the most probable second ambiguous input and the most probable first ambiguous input are redundant representations expressing the same meaning.

32. A method of training a speech recognizer, comprising:

prompting a user to make an utterance comprising a series of symbols, each said symbol consisting of one of a letter, digit, and punctuation,

recognizing said utterance, and

calculating the probability of confusing each symbol of the recognized utterance with the symbol in the corresponding digit place of the prompted utterance.

33. The method of claim 32 wherein said probability is calculated within the context of the preceding symbol or silence.

34. A method of displaying word choices during speech recognition, comprising:

recognizing an uttered word,

recognizing an uttered spelling of a prefix of the uttered word, whereby symbols are used to spell said prefix, and

displaying a list of word choices on a screen for selection, a top choice on the list corresponding to a highest ranked choice.

35. The method of claim 34 wherein said symbols comprise letters, digits, and punctuation.

36. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances, including

creating a list of hypothesized possible utterances that relate to at least one of said recognized spoken utterances based on said stored data, and

creating and ranking a list of possible utterances based upon how closely each of the possible utterances corresponds to one of said spoken utterances and comparing said ranked list of possible utterances to said list of hypothesized possible utterances for commonality between said lists.

37. A method of speech recognition including:

recognizing a first spoken utterance by continuous recognition to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances, including

creating a list of possible first utterances that may be confused with said recognized first utterance.

38. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining the most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances,

wherein said first spoken utterance comprises a zipstate and said second spoken utterance comprises a city from a destination address on a package, said determination of the most probable first and second utterances resulting in the sorting of said package according to the package'"'"'s destination address.

39. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining the most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances,

wherein said first spoken utterance comprises a word and said second spoken utterance comprises spelled prefix including ordered symbols.

40. A method of generating a choice list from a continuously recognized utterance comprising:

recognizing a spoken utterance to identify a recognized first utterance corresponding to the spoken utterance,

consulting stored information to determine the probability of confusing possible utterances in the stored information with said recognized utterance,

producing a list of possible utterances from the stored information that could be confused with the recognized utterance, and

rerecognizing said spoken utterance against a merged list of said list of possible utterances and said recognized utterance to create a ranked list of possible utterances having a ranking based upon how closely each utterance in said merged list corresponds to said spoken utterance.

41. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance,

determining most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances, wherein the most probable second utterance contains information that is semantically related to the most probable first utterance, and

creating a list of possible utterances that could be confused with at least one of said recognized utterances.

42. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances, wherein the most probable second utterance contains information that is semantically related to the most probable first utterance,

wherein said first spoken utterance comprises a word and said second spoken utterance comprises spelled prefix including ordered symbols, the method further including creating a list of possible prefixes that could be confused with said recognized second utterance.

43. A method of speech recognition including:

recognizing a first spoken utterance to identify a recognized first utterance corresponding to the first spoken utterance,

recognizing a second spoken utterance having information that is related to said first spoken utterance to identify a recognized second utterance corresponding to the second spoken utterance, and

determining most probable first and second utterances based on the recognized first and second utterances and on stored data about valid relationships between possible first and second utterances, wherein the most probable second utterance contains information that is semantically related to the most probable first utterance,

wherein said first spoken utterance comprises a spelled word and said second spoken utterance comprises spelled prefix including ordered symbols, said determination of the most probable first and second utterances results in recognizing said spelled word.