Connected Digit Speech Recognition Based On Mutual Information Estimation

Connected digit speech recognition is a crucial branch of continuous speech recognition.It has a long time attracted the attentions of many researchers because it has wide applications such as speech autodialer,personal number verification, etc.Mandarin connected digit speech recognition, for its own pronunciation characteristic's more difficult than English digit recognition.Each unit of a speech recognition system is studied in this paper,which includes the preprocessing,the training of reference patterns,the connected digit speech recognition algorithm and the postprocessing of confusing pairs.The research of endpoint detection includes the endpoint detection not only in the quiet environment but also in the low signal-to-noise(SNR) situation.As far as the training of the reference patterns is concerned,the modified K-means algorithm is adopted.The most important part of this paper is the research of connected speech recognition algorithm.Two kinds of algorithm are put forward,which are based on the existing fruit of Mutual-Information Match theory. The proposed algorithm is effective which is proved by theresult of experiment. Tone model and the segmentation of the consonant and vowel are adopted in the postprocessing unit to reduce the error rates of the confusing pairs of Mandarin digits.Some ideas for the improving of the system are put forward in the last chapter.