CONFIDENCE MEASURE GENERATION FOR SPEECH RELATED SEARCHING

• US 20120185252A1
• Filed: 03/23/2012
• Published: 07/19/2012
• Est. Priority Date: 08/03/2007
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Wang, Ye-Yi, Ju, Yun-Cheng, Yu, Dong
• Granted Patent: US 8,793,130 B2
• Time in Patent Office: Days
• US Class Current: 704/251
• CPC Class Codes: G10L 15/1822 Parsing for meaning understanding

Abstract

A method of generating a confidence measure generator is provided for use in a voice search system, the voice search system including voice search components comprising a speech recognition system, a dialog manager and a search system. The method includes selecting voice search features, from a plurality of the voice search components, to be considered by the confidence measure generator in generating a voice search confidence measure. The method includes training a model, using a computer processor, to generate the voice search confidence measure based on selected voice search features.

Claims

1. A method of generating a confidence measure generator for use in a voice search system, the voice search system including voice search components comprising a speech recognition system, a dialog manager and a search system, the method comprising:

selecting voice search features, from a plurality of the voice search components, to be considered by the confidence measure generator in generating a voice search confidence measure; and

training a model, using a computer processor, to generate the voice search confidence measure based on selected voice search features.

2. The method of claim 1, wherein selecting voce search features comprises:

selecting a set of features;

calculating an error rate for the model based on the set of features;

identifying insignificant features in the set of features; and

removing the insignificant features from the set of features to obtain a set of remaining features.

3. The method of claim 2, wherein selecting voice search features further comprises:

repeating the steps of selecting a set of features, calculating an error rate for the model based on the set of features, identifying insignificant features in the set of features, and removing the insignificant features from the initial set of features to obtain a set of remaining features, until a desired set of remaining features is obtained.

4. The method of claim 3, wherein identifying insignificant features comprises:

calculating how much each feature in the set of features affects the error rate of the model; and

identifying, as insignificant features, those features in the set of features that affect the error rate of the model less than a threshold amount.

5. The method of claim 4, wherein calculating how much each feature in the set of features affects the error rate of the model comprises:

selecting a feature from the set of features; and

calculating an error rate of the model without considering the selected feature.

6. The method of claim 2, wherein selecting voice search features further comprises:

determining whether each feature in the set of remaining features varies sufficiently linearly with respect to an error rate of the voice search system; and

for each given feature that does not vary sufficiently linearly, quantizing the given feature.

7. The method of claim 6, wherein determining whether each feature in the set of remaining features varies sufficiently linearly with respect to an error rate of the voice search system, comprises:

selecting a feature from the set of remaining features;

calculating voice search system error rate relative to a value of the selected feature; and

calculating a linearity measure indicative of a linearity of the selected feature.

8. The method of claim 1, wherein selecting voice features comprises:

selecting combined voice features based on combinations of the voice search features from the voice search components.

9. A computer readable storage medium storing instructions, which, when executed by a computer, perform steps that generate a confidence measure generator for use in a voice search system, the voice search system including voice search components comprising a speech recognition system, a dialog manager and a search system, the steps comprising:

selecting voice search features, from a plurality of the voice search components, to be considered by the confidence measure generator in generating a voice search confidence measure; and

training a model to generate the voice search confidence measure based on selected voice search features.

10. The computer readable storage medium of claim 9, wherein selecting voce search features comprises:

selecting a set of features;

calculating an error rate for the model based on the set of features;

identifying insignificant features in the set of features; and

removing the insignificant features from the set of features to obtain a set of remaining features.

11. The computer readable storage medium of claim 10, wherein selecting voice search features further comprises:

repeating the steps of selecting a set of features, calculating an error rate for the model based on the set of features, identifying insignificant features in the set of features, and removing the insignificant features from the initial set of features to obtain a set of remaining features, until a desired set of remaining features is obtained.

12. The computer readable storage medium of claim 11, wherein identifying insignificant features comprises:

calculating how much each feature in the set of features affects the error rate of the model; and

identifying, as insignificant features, those features in the set of features that affect the error rate of the model less than a threshold amount.

13. The computer readable storage medium of claim 12, wherein calculating how much each feature in the set of features affects the error rate of the model comprises:

selecting a feature from the set of features; and

calculating an error rate of the model without considering the selected feature.

14. The computer readable storage medium of claim 10, wherein selecting voice search features further comprises:

determining whether each feature in the set of remaining features varies sufficiently linearly with respect to an error rate of the voice search system; and

for each given feature that does not vary sufficiently linearly, quantizing the given feature.

15. The computer readable storage medium of claim 14, wherein determining whether each feature in the set of remaining features varies sufficiently linearly with respect to an error rate of the voice search system, comprises:

selecting a feature from the set of remaining features;

calculating voice search system error rate relative to a value of the selected feature; and

calculating a linearity measure indicative of a linearity of the selected feature.

16. The computer readable storage medium of claim 9, wherein selecting voice features comprises:

selecting combined voice features based on combinations of the voice search features from the voice search components.