Embedded wavelet analysis of non-audible signals

Abstract

The analysis of non-audible signals has gained a significant importance due to their many fields of application, among them, speech synthesis for people with speech disabilities. This analysis can be used to acquire information from the vocal apparatus without the need of speaking in order to produce a phonetic expression. The analysis of a Wavelet transformation of Spanish words recorded through a non-audible murmur microphone in order to achieve an embedded silent speech recognition system of Spanish language is proposed. A non-audible murmur microphone is used as sensor of non-vocal speech. Coding of the input data is done through a Wavelet transform using a fourth-order Daubechies function. The acquisition, processing and transmission system is applied through a STM32F4-Discovery evaluation board. The used vocabulary consists of command words aimed to control mobile robots or human-machine interfaces. The Wavelet transformation of four Spanish words, each of them having five independent samples, was accomplished. An analysis of the resulting data was performed, and features as average, peaks and frequency were distinguished. The processing of the signals is performed successfully and further work in speech activity detection and features classifiers is proposed.