System and method for processing speech recognition

• US 8,571,861 B2
• Filed: 11/30/2012
• Issued: 10/29/2013
• Est. Priority Date: 10/13/2000
• Status: Expired due to Term

• Current Assignee: Interactions, LLC
• Original Assignee: AT&T Intellectual Property II LP (AT&T, Inc.)
• Inventors: Narayanan, Shrikanth Sambasivan, Rose, Richard C., Parthasarathy, Sarangarajan, Rosenberg, Aaron Edward
• Primary Examiner(s): ALBERTALLI, BRIAN LOUIS
• Application Number:
  US13/690,636
• Publication Number:
  US 20130090928A1
• Time in Patent Office: 333 Days
• Field of Search: None
• US Class Current: 704/233
• CPC Class Codes: G10L 15/04 Segmentation; Word boundary detection
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 15/197 Probabilistic grammars, e.g. word n-grams
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 2015/0631 Creating reference templates; Clustering

Abstract

An automatic speech recognition (ASR) system and method is provided for controlling the recognition of speech utterances generated by an end user operating a communications device. The ASR system and method can be used with a mobile device that is used in a communications network. The ASR system can be used for ASR of speech utterances input into a mobile device, to perform compensating techniques using at least one characteristic and for updating an ASR speech recognizer associated with the ASR system by determined and using a background noise value and a distortion value that is based on the features of the mobile device. The ASR system can be used to augment a limited data input capability of a mobile device, for example, caused by limited input devices physically located on the mobile device.

Claims

1. A method comprising:

receiving a speech utterance from a client device, the speech utterance spoken by a user;

identifying a location associated with the speech utterance;

determining, by accessing a profile of the user, a probability associated with the user and the location, the probability being an expected type of background noise for the user at the location; and

based on the probability, applying a background noise model to recognize the speech utterance.

2. The method of claim 1, wherein the client device is a mobile device.

3. The method of claim 1, wherein determining the probability is based on accessing a stored series of background noises from a background environment associated with the user.

4. The method of claim 1, wherein applying the background noise model comprises compensating a speech recognition model with the background noise model.

5. The method of claim 1, wherein applying the background noise model is performed based on characteristics of the client device.

6. The method of claim 1, further comprising:

identifying a time associated with the speech utterance; and

determining the probability based on the time.

7. A system comprising:

a processor; and

a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising;

receiving a speech utterance from a client device, the speech utterance spoken by a user;

identifying a location associated with the speech utterance;

determining, by accessing a profile of the user, a probability associated with the user and the location, the probability being an expected type of background noise for the user at the location; and

based on the probability, applying a background noise model to recognize the speech utterance.

8. The system of claim 7, wherein the client device is a mobile device.

9. The system of claim 7, wherein determining the probability is based on accessing a stored series of background noises a background environment associated with the user.

10. The system of claim 7, wherein applying the background noise model comprises compensating a speech recognition model with the background noise model.

11. The system of claim 7, wherein applying the background noise model is performed based on characteristics of the client device.

12. The system of claim 7, the computer-readable storage medium having additional instructions stored which result in the operations further comprising:

identifying a time associated with the speech utterance; and

determining the probability based at least in part on the time.

13. A computer-readable storage device having instructions stored which, when executed by a processor, cause the processor to perform operations comprising:

receiving a speech utterance from a client device, the speech utterance spoken by a user;

identifying a location associated with the speech utterance;

determining, by accessing a profile of the user, a probability associated with the user and the location, the probability being an expected type of background noise for the user at the location; and

based on the probability, applying a background noise model to recognize the speech utterance.

14. The computer-readable storage device of claim 13, wherein the client device is a mobile device.

15. The computer-readable storage device of claim 13, wherein determining the probability is based on accessing a stored series of background noises from a background environment associated with the user.

16. The computer-readable storage device of claim 13, wherein applying the background noise model comprises compensating a speech recognition model with the background noise model.

17. The computer-readable storage device of claim 13, wherein applying the background noise model is performed based on characteristics of the client device.