Speech Recognizer Library
The Speech Recognizer Library implements a fixed-point speaker-dependent speech recognizer targeted toward embedded processors. The library provides easy-to-use APIs that can voice enable applications. Resources in addition to the library include an example project illustrating the use of MinHMM.
Prior to using a speaker-dependent speech recognizer, the user must train the recognizer with each phrase to recognize by speaking the phrase several times. During training, the recognizer creates a model of each phrase to use during the recognition process. The performance of the recognizer is thus tied to the speaker that trained each phrase. If another speaker tries to use the recognizer, performance will likely degrade due to differences in the way the phrase is spoken.
The Speech Recognizer Library software provides a comprehensive set of APIs for speaker-dependent speech recognition for a wide variety of embedded applications. Speech Recognizer APIs allow an application to perform the following operations.
- Create speaker-defined phrase models
- Train a phrase model with additional audio data to improve performance
- Delete a model
- Enable or disable specific models during recognition search
- Obtain information about a model
- Run recognition search
- Set parameters to tune recognizer performance.
- Optional write/read model data to/from a file
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