Dynamic and adaptive selection of vocabulary and acoustic models based on a call context for speech recognition

• US 20030191639A1
• Filed: 04/05/2002
• Published: 10/09/2003
• Est. Priority Date: 04/05/2002
• Status: Abandoned Application

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Mazza, Sam
• Application Number:
  US10/115,936
• Publication Number:
  US 20030191639A1
• Time in Patent Office: Days
• US Class Current: 704/231
• CPC Class Codes: G10L 15/183 using context dependencies, e.g. language models
• CPC Class Codes: G10L 2015/228 of application context

Abstract

An arrangement is provided for dynamic and adaptive selection of vocabulary and acoustic models based on a call context for speech recognition. When a call is received from a caller who is associated with a customer, relevant call information associated with the call is forwarded and used to detect a call context. At least one vocabulary is selected based on the call context. Acoustic models with respect to each selected vocabulary are identified based on the call context. The vocabulary and the acoustic models are then used to recognize the speech content of the call from the caller. Reservation of Copyright

This patent document contains information subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent, as it appears in the U.S. Patent and Trademark Office files or records but otherwise reserves all copyright rights whatsoever.

Claims

1. A method, comprising:

receiving a call from a caller associated with a customer;

fowarding relevant call information associated with the call;

detecting a call context associated with the call based on the call information;

selecting at least one vocabulary according to the call context;

identifying at least one acoustic model for each of the at least one vocabulary based on the call context; and

recognizing speech content of the call using the at least one vocabulary and the at least one acoustic model.

2. The method according to claim 1, wherein

the at least one vocabulary includes at least some of:

a digits vocabulary in a particular language,

a letter vocabulary in a particular language,

a word vocabulary in a particular language, and

a generic vocabulary in a particular language; and

the at least one acoustic model representing a specific accent with respect to a particular vocabulary.

3. The method according to claim 2, wherein the call context includes at least some of:

geographical information associated with the call which includes;

an area code representing a geographical area from where the call is placed,

an exchange number representing a geographical region from where the call is placed, or

a caller identification number representing a phone through which the call is placed by the caller;

customer information associated with the customer which includes;

an account number representing an account using which the customer places the call,

the caller identification number associated with the account;

customer characteristics;

or

an on-the-fly voice sample used to evaluate voice characteristics.

4. The method acording to claim 3, wherein the customer characteristics associated with the customer include at least some:

gender of at least one caller associated with the customer;

zero or more languages for communication preferred by the at least one caller;

or

speech accent with respect to the preferred languages of the at least one caller.

5. The method according to claim 4, wherein said detecting a call context comprises at least some of:

extracting the geographical information of the call from the relevant call information associated with the call;

identifying the customer information from a customer profile corresponding to the account number using which the customer places the call;

or

identifying the customer characteristics based on the speech of the customer.

6. The method according to claim 1, further comprising:

accessing the performance of said recognizing;

re-selecting at least some of the vocabulary and the acoustic models that correspond to better performance of said recognizing according to said assessing.

7. A method for selecting an appropriate vocabulary, comprising:

receiving call information relevant to a call placed by a caller associated with a customer;

retrieving, if the call information provides appropriate identification, a customer profile, accessed using the appropriate identification, to obtain customer information;

detecting a call context associated with the call based on the call information and the customer information; and

selecting an appropriate vocabulary based on the call context.

8. The method according to claim 7, wherein said detecting comprises:

extracting geographical or customer information from the call information;

obtaining customer information from the customer profile;

or

detecting caller characteristics based on the speech of the caller.

9. A method for selecting an appropriate acoustic model, comprising:

receiving a call context, relevant to a call placed by a caller associated with a customer, and a vocabulary; and

selecting at least one acoustic model with respect to the vocabulary based on the a call context.

10. The method according to claim 9, wherein said selecting includes at least some of:

analyzing relevant customer information contained in the a call context; and

determining the speech characteristics of the caller from the speech of the caller.

11. A method for adaptively adjusting vocabulary and acoustic model selection, comprising:

performing speech recognition using at least one vocabulary and associated at least one acoustic model, selected according to a call context related to a call from a caller, on the speech from the caller;

assessing the performance of the speech recognition with respect to each of the at least one vocabulary and each of its associated acoustic models; and

re-selecting an updated vocabulary or an updated acoustic model based on assessed speech recognition performance so that said performing speech recognition is to be carried out using the updated vocabulary and the updated acoustic model.

12. The method system according to claim 11, further comprising:

updating a customer profile, associated with the caller, based on the updated acoustic model.

13. A system, comprising:

a caller for making a call; and

a speech recognition mechanism for recognizing the speech of the caller using at least one vocabulary and at least one acoustic model selected adaptively based on a call context associated with the call and the caller.

14. The system according to claim 13, wherein the speech recognition mechanism comprises:

a vocabulary adaptation mechanism for detecting the call context and for adaptively selecting the at least one vocabulary based on the detected call context;

an acoustic model adaptation mechanism for dynamically selecting the at least one acoustic model that are adaptive to the call context and the caller so that the performance of the speech recognition mechanism is optimized;

an automatic speech recognizer for performing speech recognition on the speech of the caller using the at least one vocabulary and the at least one acoustic model.

15. A vocabulary selection mechanism, comprising:

a call context detection mechanism for detecting a call context based on relevant information associated with a call from a caller; and

a vocabulary selection mechanism for selecting an appropriate vocabulary based on the call context.

16. The mechanism according to claim 15, wherein the call context detection mechanism detects the call context based on at least some of:

geographical information associated with the call;

customer information from a customer profile to which the caller is associated with; and

acoustic characteristics associated with the caller and detected from the speech of the caller.

17. An acoustic model adaptation mechanism, comprising:

an acoustic model selection mechanism for adaptively selecting at least one acoustic model based on a call context of a call placed by a caller; and

an adaptation mechanism for dynamically updating the acoustic model selection made by the acoustic model selection mechanism based on the performance of an automatic speech recognizer to generate an updated acoustic model.

18. The mechanism according to claim 17, wherein the adaptation mechanism updates a customer profile associated with the caller based on the updated acoustic model.

19. A machine-accessible medium encoded with data, the data, when accessed, causing:

receiving a call from a caller associated with a customer;

fowarding relevant call information associated with the call;

detecting a call context associated with the call based on the call information;

selecting at least one vocabulary according to the call context;

identifying at least one acoustic model for each of the at least one vocabulary based on the call context; and

recognizing speech content of the call using the at least one vocabulary and the at least one acoustic model.

20. The medium according to claim 19, wherein the at least one vocabulary includes at least some of:

a digits vocabulary in a particular language,

a letter vocabulary in a particular language,

a word vocabulary in a particular language, and

a generic vocabulary in a particular language; and

the at least one acoustic model representing a specific accent with respect to a particular vocabulary.

21. The medium according to claim 20, wherein the call context includes at least some of:

geographical information associated with the call which includes;

an area code representing a geographical area from where the call is placed,

an exchange number representing a geographical region from where the call is placed, or

a caller identification number representing a phone through which the call is placed by the caller;

customer information associated with the customer which includes;

an account number representing an account using which the customer places the call,

the caller identification number associated with the account;

or

customer characteristics.

22. The medium acording to claim 21, wherein the customer characteristics associated with the customer include at least some:

gender of at least one caller associated with the customer;

zero or more languages for communication preferred by the at least one caller;

or

speech accent with respect to the preferred languages of the at least one caller.

23. The medium according to claim 22, wherein said detecting a call context comprises at least some of:

extracting the geographical information of the call from the relevant call information associated with the call;

identifying the customer information from a customer profile corresponding to the account number using which the customer places the call;

or

identifying the customer characteristics based on the speech of the customer.

24. The medium according to claim 19, the data, when accessed, further causing:

accessing the performance of said recognizing;

re-selecting at least some of the vocabulary and the acoustic models that correspond to better performance of said recognizing according to said assessing.

25. A machine-accessible medium encoded with data for selecting an appropriate vocabulary, the data, when accessed, causing:

receiving call information relevant to a call placed by a caller associated with a customer;

retrieving, if the call information provides appropriate identification, a customer profile, accessed using the appropriate identification, to obtain customer information;

detecting a call context associated with the call based on the call information and the customer information; and

selecting an appropriate vocabulary based on the call context.

26. The medium according to claim 25, wherein said detecting comprises:

extracting geographical or customer information from the call information;

obtaining customer information from the customer profile;

or

detecting caller characteristics based on the speech of the caller.

27. A machine-accessible medium encoded with data for selecting an appropriate acoustic model, the data, when accessed, causing:

receiving a call context, relevant to a call placed by a caller associated with a customer, and a vocabulary; and

selecting at least one acoustic model with respect to the vocabulary based on the call context.

28. The medium according to claim 27, wherein said selecting includes at least some of:

analyzing relevant customer information contained in the call context; and

determining the speech characteristics of the caller from the speech of the caller.

29. A machine-accessible medium encoded with data for adaptively adjusting vocabulary and acoustic model selection, the data, when accessed, causing:

performing speech recognition using at least one vocabulary and associated at least one acoustic model, selected according to a call context related to a call from a caller, on the speech from the caller;

assessing the performance of the speech recognition with respect to each of the at least one vocabulary and each of its associated acoustic models; and

re-selecting an updated vocabulary or an updated acoustic model based on assessed speech recognition performance so that said performing speech recognition is to be carried out using the updated vocabulary and the updated acoustic model.

30. The medium system according to claim 29, the data, when accessed, further causing:

updating a customer profile, associated with the caller, based on the updated acoustic model.