Speech and Speaker Recognition System Using Artificial Neural Networks and Hidden Markov Model

Aiming towards automatic machine learning by human, a methodology for speech recognition with speaker identification based on Hidden Markov Model for security is a demand of science. Inspiring by the same, we propose a methodology to identify speaker and detection of speech. Within our research acquisition of speech signal, analysis of spectrogram, neutralization, extraction of features for recognition, mapping of speech using Artificial Neural networks is presented. In our investigation such a method of mapping is realized using back propagation rules of neural networks. This algorithm is especially suitable for huge set of input and output speech mapping. Additionally recognition of speaker using Hidden Markov Model also will be presented in this paper.