Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition
Reexamination Certificate
2000-02-10
2002-04-23
Dorvil, Richemond (Department: 2641)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Recognition
C704S255000
Reexamination Certificate
active
06377924
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to speech recognition and more particularly to enrollment of voice commands which can be recognized to trigger actions.
BACKGROUND OF THE INVENTION
There is a growing demand for voice commands recognition. It has been used for voice name dialing for telephone and user-specific commands such as car controls, computer operations and almost everything that would use the hands to trigger an action. It is even being considered for browsing the Internet. It is the accuracy of the recognition that is important and that is dependent on models generated during enrollment. The recognition of voice commands requires the construction of HMM models on enrollment, during which utterance is recorded and need to build the HMM of the command. Depending on the model level, two types of HMMs can be used. A first and most common type is word-based models which models the whole command (may be several words as a single unit). The second type is phone-based which uses a concatenation of phone-like sub-word units to model a command. The sub-word unit can be represented using speaker-independent HMM as described by N. Jain, R. Cole and E. Barnard in article entitled “Creating Speaker-Specific Phonetic Templates with Speaker-Independent Phonetic Recognizer”; In Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, page 881-884, Atlanta, May 1996, or speaker specific HMM. While word-based HMMs is easier to train, phone-based HMM has many advantages including various degree of distribution tying and rejection based on phone durations.
SUMMARY OF THE INVENTION
In accordance with one embodiment of the present inventions applicants teach the construction of phone-based HMM for speaker-specific command enrollment comprising the steps of providing a set (H) of speaker-independent phone-based HMMs, providing a gammer (G) comprising a loop of phones with optional between phone silence (BWS) and two utterance (U
1
and U
2
) of the command produced by the enrollment speaker and wherein the first frames of the first utterance containing only background noise, generating a sequence of phone-like unit HMMS and generating the number of HMMs in that sequence.
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Neena Jian, et al., “Creating Speaker-Specific Phonetic Templates with a Speaker-Independent Phonetic Recognizer: Implications for Voice Dialing” IEEE, pp. 881-884, 1996.
Gong Yifan
Ramalingam Coimbatore S.
Dorvil Richemond
McFadden Susan
Telecky , Jr. Frederick J.
Texas Instruments Incorporated
Troike Robert L.
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