System, method and computer program product for spelling fallback during large-scale speech recognition

• US 20030149565A1
• Filed: 03/09/2001
• Published: 08/07/2003
• Est. Priority Date: 03/09/2001
• Status: Abandoned Application

• Current Assignee: Bevocal Incorporated (Microsoft Corporation)
• Original Assignee: Bevocal Incorporated (Microsoft Corporation)
• Inventors: Chang, Steve S., Damiba, Bertrand A.
• Application Number:
  US09/802,435
• Publication Number:
  US 20030149565A1
• Time in Patent Office: Days
• US Class Current: 704/250
• CPC Class Codes: G10L 15/18 using natural language modelling

Abstract

A system, method and computer program product are provided for recognizing utterances. Initially, an utterance is recognized. Thereafter, it is determined whether the utterance can be recognized utilizing speech recognition. If the utterance can not be recognized utilizing speech recognition, spelling recognition is used to recognize the utterance.

Claims

1. A method for recognizing utterances, comprising the steps of:

(a) receiving an utterance;

(b) determining whether the utterance can be recognized utilizing speech recognition; and

(c) utilizing spelling recognition to recognize the utterance if the utterance can not be recognized utilizing speech recognition.

2. The method as recited in claim 1, and further comprising the step of parsing the utterance into components.

3. The method as recited in claim 2, wherein the utterance is pars ed into components utilizing speech recognition.

4. The method as recited in claim 2, wherein the user is prompted to parse the utterance into components.

5. The method as recited in claim 4, wherein the parsed components are received utilizing utterances.

6. The method as recited in claim 4, wherein the parsed components are received utilizing at least one of DTMF signals and spoken spelling sounds.

7. The method as recited in claim 2, wherein the components include letters.

8. The method as recited in claim 2, and further comprising the step of utilizing speech recognition to recognize at least one of the components of the utterances.

9. The method as recited in claim 8, wherein the speech recognition utilizes models of multiple components.

10. The method as recited in claim 2, and further comprising the step of comparing the at least one component of the utterance with a database of grammars.

11. The method as recited in claim 10, and further comprising the step of outputting the grammars that match based on the comparison.

12. The method as recited in claim 11, and further comprising the step of prompting a user for more information if a number of outputted grammars is greater than a predetermined amount.

13. The method as recited in claim 12, wherein the information includes additional component.

14. The method as recited in claim 11, and further comprising the step of allowing the user to select between the outputted grammars.

15. The method as recited in claim 14, wherein the user is allowed to select between the grammars utilizing additional utterances.

16. The method as recited in claim 14, wherein the user is allowed to select between the grammars utilizing at least one of DTMF signals and spoken spelling sounds. .

17. The method as recited in claim 1, wherein the utterance is representative of a street name.

18. A computer program product for recognizing utterances, comprising:

(a) computer code for receiving an utterance;

(b) computer code for determining whether the utterance can be recognized utilizing speech recognition; and

(c) computer code for utilizing spelling recognition to recognize the utterance if the utterance can not be recognized utilizing speech recognition.

19. A system for recognizing utterances, comprising:

(a) logic for receiving an utterance;

(b) logic for determining whether the utterance can be recognized utilizing speech recognition; and

(c) logic for utilizing spelling recognition to recognize the utterance if the utterance can not be recognized utilizing speech recognition.