VQ Combined With HMM Model Experimental Study On Speech Signal

Humans have been dreaming through direct language can make all sorts of corresponding machine, in order to finish the work under special environment. But, in the very long time, can not achieve the dream. Until today, the information age of computer science and related disciplines for the rapid development of the human dream provides efficient means of realization, make the machine understanding human language, the language of the machine understanding speech signal analysis & identification technique, technique.Nearly two years, the rapid development of human society in speech signal analysis is increasingly high recognition technology, and the requirements for the advancement of science and technology of speech signal analysis to identify technology provides all aspects of the theory and technology support, make the speech signal analysis made significant progress in identifying technology, start from the lab to the market. In the near future, the speech signal analysis to identify technology will enter industry, electrical appliances, communications, automotive electronics, medical, family service, consumer electronic products such as production all spheres of life.Based on the analysis of the speech signal recognition principle and basic technical basis, through the markov model (HMM) and vector quantization model (VQ), according to the study and analysis of the modeling ability strong HMM, but the ability to identify the influence by environment, While vector quantization model ability is not strong, but because, although the vector similarity makes it good ability to identify, This study analyzed the advantages and disadvantages of both in put forward, based on the new model and algorithm. At the same time, according to the experimental conditions, choose Mel parameters as recognition characteristic parameters. In the new model is established, the speech recognition system, the selection of the speech signal of speech signal feature extraction and recognition of speech signal analysis. Under the same conditions, the analysis of the same speech signal recognition results and the analysis of the model identification results HMM compares the results of recognition, joint model is higher than single HMM model, the joint model has better performance than the HMM model, And to further establish joint model is applied in the designated specimen, designated speech signal, not specified sample not specified semantic signal the three cases, joint model experiment, the stability of the performance of joint model is reliable, the operation is in good condition...