Speech visualization based on wavelet transform
基于小波变换的语音信号可视化研究*

This paper described a new speech visualization method that created readable patterns by integrating combined feature into a single image. The system made use of time-frequency analysis based on wavelet transform to simulate the band-pass filter property of basilar membrane. The method remedied the defect that short fourier transform(SFT) had the same time-resolution and frequency-resolution to different frequency ranges. The auditory feature was displayed on the CRT by plot patterns and the deaf could utilize their own brain to identify different speech for training their oral ability effectively. Firstly, speech signal underwent a series of preprocessing course. Secondly, made use of wavelet transform to process time-frequency analysis for speech signal and extracted the feature value for speech visualization. Then calculated that the feature value lay in which place in full array and obtained the combined feature value. Finally, utilized plot display algorithm to generate a speech plot.