Claims
- 1. A computer-based method of routing an utterance to a system, the method comprising:
receiving an utterance including two or more words; processing the utterance using large-vocabulary continuous speech recognition to generate a string of text corresponding to the utterance; generating a confidence estimate of the string of text corresponding to the utterance; comparing the confidence estimate to a predetermined threshold; if the confidence estimate satisfies the predetermined threshold, forwarding the string of text to the system; and if the confidence estimate does not satisfy the predetermined threshold, forwarding information relating to the utterance to a transcriptionist.
- 2. The method of claim 1 further comprising if the confidence estimate does not satisfy the predetermined threshold, having the transcriptionist determine an acceptable string of text and forwarding the acceptable string of text to the system.
- 3. The method of claim 1 in which the confidence estimate indicates a probability that the string of text is an acceptable representation of the utterance.
- 4. The method of claim 1 in which the information relating to the utterance comprises one or more of: the utterance, the string of text corresponding to the utterance, and the generated confidence estimate of the string of text.
- 5. The method of claim 1 in which generating the confidence estimate comprises:
selecting one or more predictors relating to the large-vocabulary continuous speech recognition; and training a confidence model using the one or more predictors.
- 6. The method of claim 5 in which generating the confidence estimate comprises:
extracting values of the one or more predictors based on the received utterance; and providing the extracted values to the confidence model to generate the confidence estimate.
- 7. The method of claim 1 further comprising:
comparing the confidence estimate to a second predetermined threshold; and if the confidence estimate does not satisfy the first predetermined threshold and does satisfy the second predetermined threshold level:
forwarding the information relating to the utterance to the user who spoke the utterance, and permitting the user to act in response to the forwarded information.
- 8. The method of claim 1 in which the transcriptionist is a human transcriptionist.
- 9. The method of claim 1 in which the system includes a human recipient.
- 10. A computer-based method of routing a message to a system, the method comprising:
receiving a message including utterances; processing each utterance in the message using large-vocabulary continuous speech recognition to generate a string of text corresponding to that utterance; generating a confidence estimate for each string of text that corresponds to an utterance; comparing each confidence estimate to a predetermined threshold; if all of the confidence estimates satisfy the predetermined threshold, forwarding the string of text to the system; and if any one of the confidence estimates does not satisfy the predetermined threshold level, forwarding the message to a transcriptionist.
- 11. The method of claim 10 in which a confidence estimate for a string of text indicates a probability that the string of text is an acceptable representation of the corresponding utterance.
- 12. The method of claim 10 further comprising, if any one of the confidence estimates does not satisfy the predetermined threshold, having the transcriptionist determine acceptable strings of text for the message and forwarding the acceptable strings of text for the message to the system.
- 13. The method of claim 10 in which generating the confidence estimate for a string of text comprises:
selecting one or more predictors for the string of text based on the large-vocabulary continuous speech recognition; and training a confidence model for the string of text using the one or more predictors.
- 14. The method of claim 13 in which generating the confidence estimate for a string of text comprises:
extracting values of the one or more predictors for the string of text based on the corresponding utterance; and providing the extracted values for the utterance to the confidence model to generate the confidence estimate for the string of text.
- 15. The method of claim 10 further comprising:
comparing each confidence estimate to a second predetermined threshold; and if a confidence estimate does not satisfy the first predetermined threshold level and satisfies the second predetermined threshold level:
forwarding information relating to the message to the user who spoke the message, and permitting the user to act in response to the forwarded information.
- 16. The method of claim 15 in which the information relating to the message comprises one or more of: the message, the string of text for the confidence estimate, and the confidence estimate for the string of text.
- 17. The method of claim 10 in which the transcriptionist is a human transcriptionist.
- 18. The method of claim 10 in which the system includes a human recipient.
- 19. The method of claim 10 in which at least one utterance in the message comprises two or more words.
- 20. A computer-based method of routing a message to a system, the method comprising:
receiving a message including utterances; processing each utterance in the message using large-vocabulary continuous speech recognition to generate a string of text corresponding to that utterance; generating a confidence estimate for each string of text that corresponds to an utterance; comparing each confidence estimate to a predetermined threshold; if all of the confidence estimates satisfy the predetermined threshold, forwarding the strings of text to the system; and if one of the confidence estimates does not satisfy the predetermined threshold, forwarding information relating to the utterance corresponding to that confidence estimate to a transcriptionist.
- 21. The method of claim 20 in which a confidence estimate for a string of text indicates a probability that the string of text is an acceptable representation of the corresponding utterance.
- 22. The method of claim 20 further comprising, if one of the confidence estimates does not satisfy the predetermined threshold, after the transcriptionist determines an acceptable string of text for the utterance, forwarding the acceptable string of text for the message to the system.
- 23. The method of claim 20 in which generating the confidence estimate for a string of text comprises:
selecting one or more predictors for the string of text based on the large-vocabulary continuous speech recognition; and training a confidence model for the string of text using the one or more predictors.
- 24. The method of claim 23 in which generating the confidence estimate for a string of text comprises:
extracting values of the one or more predictors for the string of text based on the corresponding utterance; and providing the extracted values for the utterance to the confidence model to generate the confidence estimate for the string of text.
- 25. The method of claim 20 in which the information relating to the utterance corresponding to the confidence estimate comprises one or more of: the message, the string of text for the confidence estimate, and the confidence estimate.
- 26. The method of claim 20 further comprising:
comparing each confidence estimate to a second predetermined threshold; and if any one of the confidence estimates does not satisfy the first predetermined threshold level and satisfies the second predetermined threshold level:
forwarding the information relating to the utterance that generated that confidence estimate to the user who spoke the message, and permitting the user to act in response to the forwarded information.
- 27. The method of claim 20 in which the transcriptionist is a human transcriptionist.
- 28. The method of claim 20 in which the system includes a human recipient.
- 29. The method of claim 20 in which at least one utterance in the message comprises two or more words.
- 30. A computer-based method of routing a message to a system, the method comprising:
receiving a message including utterances; processing each utterance in the message using large-vocabulary continuous speech recognition to generate a string of text for each utterance in the message; generating a confidence estimate for each string of text that corresponds to an utterance; calculating a message confidence estimate based on the confidence estimates for the strings of text generated for the message; comparing the message confidence estimate to a predetermined threshold; if the message confidence estimate satisfies the predetermined threshold, forwarding the strings of text generated for the message to the system; and if the message confidence estimate does not satisfy the predetermined threshold, forwarding information relating to the message to a transcriptionist,
- 31. The method of claim 30 in which a confidence estimate for a string of text indicates a probability that the string of text is an acceptable representation of the corresponding utterance.
- 32. The method of claim 30 further comprising, if the message confidence estimate does not satisfy the predetermined threshold, having the transcriptionist determine one or more acceptable strings of text and for the utterances of the message, forwarding the acceptable strings of text for the message to the system.
- 33. The method of claim 30 in which information relating to the message comprises one or more of: the message, the string of text for each utterance in the message, and the message confidence estimate.
- 34. The method of claim 30 in which generating the confidence estimate for a string of text comprises:
selecting one or more predictors for the string of text based on the large-vocabulary continuous speech recognition; and training a confidence model for the string of text using the one or more predictors.
- 35. The method of claim 34 in which generating the confidence estimate for a string of text comprises:
extracting values of the one or more predictors for the string of text based on the corresponding utterance; and providing the extracted values for the utterance to the confidence model to generate the confidence estimate for the string of text.
- 36. The method of claim 30 further comprising:
comparing the message confidence estimate to a second predetermined threshold; and if the message confidence estimate does not satisfy the first predetermined threshold and it satisfies the second predetermined threshold; forwarding the information relating to the message to the user who spoke the message, and permitting the user to act in response to the forwarded information.
- 37. The method of claim 30 in which the transcriptionist is a human transcriptionist.
- 38. The method of claim 30 in which the system includes a human recipient.
- 39. The method of claim 30 in which at least one utterance in the message comprises two or more words.
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims benefit of U.S. Provisional Application No. 60/210,823, filed Jun. 12, 2000, which is incorporated by reference.
Provisional Applications (1)
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Number |
Date |
Country |
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60210823 |
Jun 2000 |
US |