Research Of The Characteristics Parameters Extraction In The Personal Of Speech Recognition

With the development of the technology of computer increasingly, speech recognition is very promising in application. As an interdisciplinary field, it is also theoretically very valued.In fact, speech recognition is the process of pattern recognition. However, to ensure relative intact of speech recognition, it has close contact with the effective extraction of the voice signal characteristic parameters. Extraction of the characteristics parameters is mainly to attain the information that are able to represent voice characteristics, and reduce the amount of data to deal with during the speech recognition, so as to express the voice signal as possible as accurately. This paper analyzes the overall structure and technology of speech recognition system, researches speech signal feature extraction. It is important theoretical and practical significance for speech recognitionFirst, introduce the basic knowledge of and speech recognition. Study the preprocessing of the voice signal, feature parameter extraction algorithms, speech recognition technology and training model matching, including Dynamic Time Warping and Hidden Markov Models. Focus on the analysis of the Dynamic Time Warping algorithm used in this article. Give the overall scheme of speech signal feature parameters to extract.Secondly, gather the voice signal in the office environment, excluding directly those obvious interference was accidental and caused by its own speak of irregular samples. And then display collected voice information.Furthermore, pre-processing of speech signals. On this basis, carry out voice signal feature parameter extraction, focusing on implementing, linear prediction cepstrum coefficient and Mel frequency cepstrum coefficient. Eventually, analyze its effects to individual speech recognition in the office environment. Finally, on the basis of Mel frequency cepstrum coefficient, realizes the individual speech recognition using dynamic time warping algorithm. And then analysis the results of experimental, put forward improved algorithm of dynamic time warping algorithm.