A frequency spectral feature modeling for hidden markov model based automated speech recognition

Abstract

This paper presents an approach to the recognition of speech signal using frequency spectral information with Mel frequency for the improvement of speech feature representation in a HMM based recognition approach. A frequency spectral information is incorporated to the conventional Mel spectrum base speech recognition approach. The Mel frequency approach exploits the frequency observation for speech signal in a given resolution which results in resolution feature overlapping resulting in recognition limit. Resolution decomposition with separating frequency is mapping approach for a HMM based speech recognition system. The Simulation results show a improvement in the quality metrics of speech recognition with respect to computational time, learning accuracy for a speech recognition system. © 2010 Springer-Verlag Berlin Heidelberg.