Speech analysis based on Malvar wavelet transform

This paper presents a new pre-processing method developed with the objective to represent relevant information of a signal with a minimum number of parameters. The originality of this work is to propose a new efficient pre-processing algorithm producing acoustical vectors at a variable frame rate. The length of the speech frames is no longer fixed a priori to a constant value but results from a study of the signal stationarity. Both segmentation and signal analysis are based on Malvar wavelets since the orthogonal properties of this transform are the key to the problem of comparing measures done on frames of different lengths. Some results of speech recognition based on this preprocessing are presented.