Wav File-based Voice Feature Extraction Method To Improve Research

Fundamentals of speech recognition task is that speech is converted to the corresponding command or text, this technology has a very wide range of applications, at the same time as an interdisciplinary field, also has very important research value. In a speech recognition system, speech signal feature extraction is one of the key technology, speech feature parameter selection on the speech recognition system has great influence, especially in the speaker-independent speech recognition systems, speech feature parameters are appropriate, whether can represent the characteristics of the speech signal and as far as possible removal of between person and person, tone, speed volume differences,and it has a decisive role in the speech recognition system operating efficiency and the recognition.Based on the technology of speech recognition and speech feature parameter extraction is studied. The existing typical voice system divides the speech signal pretreatment, endpoint detection, feature extraction, pattern matching and processing aspects, and in the feature extraction stage, mainly uses the characteristic parameters of acoustic model is based on linear prediction cepstrum coefficient (LPCC) and Mel frequency cepstrum based on auditory model (MFCC) parameters. Based on human auditory phenomenon observation, found in the speech signal acceleration play situation can still be ear easily identified, and accelerated after the speech on the waveform performance is more simple, according to this phenomenon, this article aims at the accelerated after the speech signal feature parameters extraction experiments, and the extraction of speech feature parameters for the actual speech recognition effect analysis.This paper firstly introduces the technology of speech recognition and speech recognition application situation and research status at home and abroad, and then on the speech recognition principle is introduced, and the speech signal preemphasis, frames and windows, endpoint detection has done a detailed analysis. As a result of this article to the speech recognition feature extraction methods improved, then the voice characteristic parameter extraction of doing an in-depth, extraction of the improved scheme. Then using the Microsoft DirectShow technology and VS2010 integrated development environment designed to accelerate the conversion of speech signal, for follow-up experiments provide the fit of the original speech signal. The voice signal is maintained to comply with RIFF standard wav file format, convenient environment in windows processing After this, in the environment of MATLAB, using DTW matching algorithm to do the isolated word speech recognition experiment,and the normal rate of speech recognition under effect and accelerate the frequency of speech recognition performance experimental analysis has been done, the experimental conclusion. Finally, this article focuses on the research summed up and the future research prospects.