Analysis of an MFCC-based audio indexing system for efficient coding of multimedia sources

Abstract

Discrimination between speech and music signals is an important problem in efficient digital radio broadcasting, particularly for variable bit rate applications such as Internet radio. This paper presents a speech/music discrimination system based on a Mel frequency cepstral coefficient (MFCC) front end and a GMM classifier. This system can be used to select the optimum coding scheme for the current frame of an input signal without knowing a priori whether it contains speech-like or music-like characteristics. An analysis of speech and music error rates for different numbers of MFCCs (from 8 to 28) is presented. For the 46 minute evaluation database used in this experiment, an accuracy of up to 97.14% for music and 93.87% for speech can be attained.