Voice Identification Secure System by Statistical Model of Speech Signal Using Normalization Technique
Jitendra Jangir, Bablu Kumar Singh, Mohd.Insaf Ali · 2014
This paper is based on the characteristic, analysis and processing on human speech signal for generation of voice identification system using spectra correlation and real time normalization method. Speech spectrogram depicts short-term variation in intensity , frequency and magnitude in graphical form thus these contains provide much useful information about voice identification. When two user speak the word, their pronunciation is similar but not identical thus spectrogram of their speech will show similarities and differences. Many method are available for processing and recognition of speech like Hidden Markov Model, multi-space distribution (MSD) based tone modelling and using quantization method but this proposed normalisation method is simple ,less time consuming ,highly accurate process for real time speech signal . The performance of robust speech recognition mainly degraded whenever the speech signal is effected by any noise. It is required to improve the stability of speech against noise for robust recognition, which is focusing on all major levels of speech recognition: feature extraction, feature enhancement, and speech modelling.