System and method for providing a compensated speech recognition model for speech recognition
View Patent ↗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 communications 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.
1. A method of recognizing speech, the method comprising:
receiving speech utterances;
determining via a processor a probable acoustic environment of the user based on time of day;
compensating a speech recognition model based on the probable acoustic environment; and
recognizing the speech utterances using the compensated speech recognition model.
2. The method according to claim 1 , wherein compensating the speech recognition model is further based on a user profile having data related to user vocal information.
3. The method according to claim 2 , wherein the user profile further includes transducer data related to a distortion value related to a transducer used in a mobile device.
4. The method according to claim 3 , wherein the user profile further includes data related to the acoustic environmental data includes a background noise value that corresponds to an operating environment of a mobile communications device.
5. The method according to claim 1 , wherein the probable acoustic environmental is determined from information from a mobile telephone.
6. The method according to claim 1 , wherein the data of the particular acoustic environmental is received from a personal digital assistant.
7. The method according to claim 1 , wherein the probable acoustic environmental data is determined using at least one microphone in the user's environment.
8. The method according to claim 4 , wherein the user profile includes data related to a transducer and a distortion value is determined based on a difference between an actual transducer in the mobile device and a response characteristic of a transducer used to train the speech recognition model.
9. The method according to claim 1 , further comprising configuring a communications device that receives the speech utterances to select a speech recognition network.
10. The method according to claim 1 , further comprising configuring the communications device to select a specific speech recognition network.
11. A tangible computer-readable medium storing instructions for controlling a computing device to recognize speech, the instructions comprising:
receiving speech utterances;
determining a probable acoustic environment of the user based on time of day;
compensating a speech recognition model based on the probable acoustic environment; and
recognizing the speech utterances using the compensated speech recognition model.
12. The tangible computer-readable medium of claim 11 , wherein compensating the speech recognition model is further based on a user profile having data related to user vocal information.
13. The tangible computer-readable medium of claim 12 , wherein the user profile further includes transducer data related to a distortion value related to a transducer used in a mobile device.
14. The tangible computer-readable medium of claim 13 , wherein the user profile further includes data related to the acoustic environmental data includes a background noise value that corresponds to an operating environment of a mobile communications device.
15. The tangible computer-readable medium of claim 11 , wherein the probable acoustic environmental is determined from information from a mobile telephone.
16. The tangible computer-readable medium of claim 11 , wherein the probable acoustic environment is determined using at least one microphone in the user's environment.
17. The tangible computer-readable medium of claim 14 , wherein the user profile includes data related to a transducer and a distortion value is determined based on a difference between an actual transducer in the mobile device and a response characteristic of a transducer used to train the speech recognition model.
18. The tangible computer-readable medium of claim 11 , wherein in the instructions further comprise updating the speech recognition model and a pronunciation model based on a specific type of mobile communications device.
19. The tangible computer-readable medium of claim 11 , further comprising configuring a communications device that receives the speech utterances to select a speech recognition network.
20. A system for recognizing speech, the system comprising:
a module configured to control a processor to receive the speech utterance;
a module configured to control the processor to determine a probable acoustic environment of the user based on a time of day;
a module configured to control the processor to compensate a speech recognition model based on the probable acoustic environment; and
a module configured to control the processor to recognize the speech utterances using the compensated speech recognition model.