ANALYSIS AND PROPOSING A ROBUST SOURCE FEATURES FOR AUTOMATIC TEXT -INDEPENDENT SPEAKER INDEXING SYSTEM

Speaker indexing (tracking) is the task of recognizing the multiple speaker s from the given speech signal. Speaker indexing is a pattern recognition task. Every pattern recognition task is classified into three phases namely, feature extraction, training and testing phases.In this paper, we analyse and study about the major feature extraction techniques that exist andpropose robust source features for text-independent speaker indexing system. A comparative study is carried out with each existingfeature extraction techniques available with source features for speakerindexing task. Finally, we propose, source features are better than the other feature extraction techniques.