VOICE COMMAND RECOGNITION SYSTEM BASED ON MFCC AND DTW

摘要

The Voice is a signal of infinite information. Digital processing of speech signal is very important for highspeed and precise automatic voice recognition technology. Nowadays it is being used for health care, telephony military and people with disabilities therefore the digital signal processes such as Feature Extraction and Feature Matching are the latest issues for study of voice signal. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients Mel-frequency cepstral coefficients (MFCCs) are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency.This paper is divided into two modules. Under the first module feature of the speech signal are extracted in the form of MFCC coefficients and in another module the non linear sequence alignment known as Dynamic Time Warping (DTW) introduced by Sakoe Chiba has been used as features matching techniques. Since its obvious that the voice signal tends to have different temporal rate, the alignment is important to produce the better performance. This paper presents the feasibility of MFCC to extract features and DTW to compare the test patterns