R&D -> Speech Recognition
Speech Recognition

Automatic Speech Recognition (ASR), which is concerned with the problem of recognition of human speech by a machine, is the core of a natural man-machine interface. In spite of this realization, the progress in this field has not been smooth due to the inherent complexity and difficulty of the problem. Environmental noise and language structures are two important issues which highly affects the recognition performance.
Speech signal processing is the first step in developing ASR. Second step is to model those features for recognition. Broadly speaking there are three approaches used for ASR, namely:

 The acoustic-phonetic approach
 The pattern recognition approach
 The artificial intelligence approach

In these approaches, statistical pattern recognition approaches are evolved as best . Some of them are VQ (vector Quantization) and HMM  (Hidden Markov Models) .


A speaker dependent voice recognition system has been developed for drawing and manipulating geometrical figures using continuous speech. The system has the provision for accepting a new user and training his/her voice.

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