Dynamic Speech Feature Parameter Extraction Based on Fitting

Abstract

In view of the existing research of the speech feature parameter recognition, the anti noise is poor and storage capacity is larger. So, data fitting has been introduced into speech feature parameter extraction to enhance that. Combine with speech spectrum dynamic changes and the short-time energy smooth stationary of speech signal, this paper puts forward and designs a arithmetic of dynamic speech feature parameter extraction based on fitting, and constructs the feature parameter extraction and personal identification scheme. And also designs critical modules algorithm. The detail process of feature parameter extraction: firstly, it created 2-d coordinate for each frame data. Then, we use 2-d coordinate system to fit for making the fitting function is matched primary data perfectly, and get the best fitting order of each frame. Lastly, it extracts the feature parameter which has been combined with the fitting order in each frame. The arithmetic has been simulated an experiment, in order to confirm the applicability and feasibility. The results illustrates the method has preferable anti-noise performance, especially expression and storage for speech segment feature parameter show more obvious advantages. Index Terms - speech recognition, feature parameter, extraction method