Method and system for dynamic nametag scoring

• US 8,626,506 B2
• Filed: 01/20/2006
• Issued: 01/07/2014
• Est. Priority Date: 01/20/2006
• Status: Active Grant

• Current Assignee: General Motors LLC (General Motors Company)
• Original Assignee: General Motors LLC (General Motors Company)
• Inventors: Chengalvarayan, Rathinavelu, Correia, John J.
• Primary Examiner(s): Chawan, Vijay B
• Application Number:
  US11/336,081
• Publication Number:
  US 20070174055A1
• Time in Patent Office: 2,909 Days
• Field of Search: 704/243, 704251-252, 704254-255
• US Class Current: 704/243
• CPC Class Codes: G10L 15/08 Speech classification or search

Abstract

A method for dynamic nametag scoring includes receiving at least one confusion table including at least one circumstantial condition wherein the confusion table is based on a plurality of phonetically balanced utterances, determining a plurality of templates for the nametag based on the received confusion tables, and determining a global nametag score for the nametag based on the determined templates. A computer usable medium with suitable computer program code is employed for dynamic nametag scoring.

Claims

1. A method for dynamic nametag scoring comprising:

receiving at a speech recognition engine at least one confusion table stored in at least one of a mobile vehicle telematics unit or a remote server and being sorted by phoneme misrecognition and including at least one circumstantial condition including at least one of a user gender, a user dialect, a vehicle type, or a vehicle operating condition, and wherein the confusion table is based on a plurality of phonetically balanced utterances;

determining a plurality of templates for a nametag based on the received at least one confusion table by using the speech recognition engine;

selecting templates from the determined plurality of templates; and

determining a global nametag score for the nametag based on a weighting indicative of a template selection frequency, wherein more frequently selected templates are assigned higher weights and less frequently selected templates are assigned lower weights.

2. The method of claim 1 wherein determining the plurality of templates for at least one nametag comprises:

receiving a nametag utterance at a speech recognition engine;

determining at least one best template for the received nametag utterance at the speech recognition engine based on a stored model; and

modifying the best template based on at least one confusion matrix to derive a plurality of templates corresponding to the best template.

3. The method of claim 1 wherein determining the global nametag score comprises:

determining at least one template score for each template;

determining at least one weight for each template;

combining the template score and the weight to yield a weighted template score; and

calculating a linear combination of the weighted template scores for all templates associated with a particular nametag.

4. The method of claim 3 wherein determining at least one weight for each template comprises:

determining a nametag selection count;

determining that the nametag selection count meets a threshold count; and

thereafter;

determining a template selection count; and

calculating the quotient of the template selection count and the nametag selection count.

5. The method of claim 4 further comprising:

modifying the template selection count based on a nametag retrieval.

6. The method of claim 1 further comprising:

continuously updating the global nametag score based on an updated weight determination.

7. The method of claim 1 wherein the selecting step is based on at least one selection factor.

8. The method of claim 7 wherein selecting the templates based on at least one selection factor comprises:

comparing the plurality of templates to a nametag audio string based on an acoustic model;

determining at least one selection factor based on the comparison;

ranking the plurality of templates based on the selection factors; and

deleting at least one template based on the ranking.

9. A method for determining a plurality of confusion tables comprising:

receiving a plurality of test utterances in a speech recognizer including acoustic models;

generating via the speech recognizer, a plurality of component sequences based on the test utterances and at least one circumstantial condition;

determining via the speech recognizer, a confusion matrix based on the component sequences and the test utterances; and

generating a confusion table based on the confusion matrix but sorted by phoneme misrecognition, and stored in at least one of a mobile vehicle telematics unit or a remote server.

10. A method for dynamic nametag scoring comprising:

receiving at a speech recognition engine, an utterance for a nametag and at least one confusion table stored in at least one of a mobile vehicle telematics unit or a remote server and being sorted by phoneme misrecognition and including at least one circumstantial condition including at least one of a user gender, a user dialect, a vehicle type, or a vehicle operating condition; and

determining a plurality of templates for the nametag based on the received at least one confusion table by using the speech recognition engine; and

selecting templates from the determined plurality of templates.

11. The method of claim 10 wherein the selecting templates is based on at least one selection factor including at least one of a nametag score, a nametag syllable count, or a nametag phoneme count.

12. The method of claim 11 wherein the selecting templates comprises:

ranking the determined plurality of templates based on the at least one selection factor; and

deleting at least one template based on the ranking.

13. The method of claim 10, further comprising determining a global nametag score for the nametag based on a weighting indicative of a template selection frequency, wherein more frequently selected templates are assigned higher weights and less frequently selected templates are assigned lower weights.