| This paper introduces the development of speech recognition, elucidates the background and significance of the research. The application of Artificial Neural Networks(ANN) to Automatic Speech Recognition(ASR) is investigated in this thesis. The recognition of speaker-independent and isolated words is focused and three types of ANN model are presented. The related algorithms and programs are developed.The characteristics of numerical and application for the methods are illustrated by using simulation testing. Especially, the influence of some factors, such as feature parameter, number of training samples, background noise and speaker independent, is discussed. Traditional DTW is also compared with the method. Results show that ANN has a higher recognition rate and potential advantages in automatic speech recognition.At last the paper indicates the directions of improvement.Through the test and research of the actual speech recognition system——the mobile robot,adopts single output model. With the SPCE061A's voice features, samples are constituted by the encoded output of sensor group and voice teaching. And samples are gained by voice triggering. Robot trains itself with the sample group gathered during samples collection, it carries out the fundamental and exploring research for the further application of speech recognition system.. |
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