Interpretation and Estimating the Parameters of Transition Probabilities in Speech Recognition System
نویسندگان
چکیده
In this paper an attempt is made to describe the various basic aspects of speech recognition system using the pattern recognition approach. Also here a new Autoregressive Hidden Markov Model (HMM) used for the speech recognition system has been introduced. Furthermore a viterbi Algorithm function is used as pattern matching technique for finding the best suited path. The main objective of this paper is to summarize the concepts used at various stages of speech recognition system which is an exciting and challenging field.
منابع مشابه
Persian Phone Recognition Using Acoustic Landmarks and Neural Network-based variability compensation methods
Speech recognition is a subfield of artificial intelligence that develops technologies to convert speech utterance into transcription. So far, various methods such as hidden Markov models and artificial neural networks have been used to develop speech recognition systems. In most of these systems, the speech signal frames are processed uniformly, while the information is not evenly distributed ...
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