Amazigh isolated word speech recognition system using the Adaptive Orthogonal Transform Method.

This work presents a method for the automatic recognition of amazigh isolated word speech based on the orthogonal adaptive transformation by creating an adaptive operator according to the analyzed signals that extracts the characteristics of each of them to obtain a vector of minimum dimensional information characteristics that will allow the identification of voice signals with high certainty and we will make a comparison with other approaches used for speech recognition system such as principal component analysis, empirical modal decomposition and discrete wavelet transform. The experimental results show the importance of the creation of the adaptive operator which gives an added value to our approach.