Modified MFCC Algorithm for Speech Recognition

Abstract

Automatic Speech Recognition has been an active research topic for more than four decades. With the
advent of digital computing and signal processing, the problem of speech recognition was clearly posed and thoroughly
studied .These developments were complemented with an increased awareness of the advantages of conversational
systems. The goal of Automatic Speech Recognition is to develop techniques and systems that enable computers to accept
speech input. The speech recognition problem may be interpreted as speech to text conversion problem. Since the early
80’s,compact implementations of accurate, real-time speech recognizers have found wide spread applications, which
includes voice activated transcription, simplified man machine communication, aids for hearing impaired individuals
and the physically disabled telephone assistance and other man-machine interface tasks. The aim of this work is to
develop a speech recognition (SR) system based on Vector Quantization (VQ) approach. This system receives speech
inputs from users, analyzes the speech inputs, searches and matches the input speech with the pre-recorded and stored
speeches in the trained database or codebook. First the feature extraction from the speech signal is done by a
parameterization of the wave formed signal into relevant feature vectors by Mel Frequency Cepstral Coefficients (MFCC
) algorithm and Modified MFCC .This parametric form is then used by the recognition system both in training the models
and testing.