Emotion based Speaker Recognition with Vector Quantization
Shraddha Bhandavle, Rasika Inamdar and Aarti Bakshi. Article: Emotion based Speaker Recognition with Vector Quantization. IJCA Proceedings on International Conference on Electronics & Computing Technologies ICONECT:9-12, May 2014. Full text available. BibTeX
@article{key:article,
author = {Shraddha Bhandavle and Rasika Inamdar and Aarti Bakshi},
title = {Article: Emotion based Speaker Recognition with Vector Quantization},
journal = {IJCA Proceedings on International Conference on Electronics & Computing Technologies},
year = {2014},
volume = {ICONECT},
pages = {9-12},
month = {May},
note = {Full text available}
}
Abstract
Speech is a most popular biometrics nowadays used for human interaction. An emotion is a mental and a physiological state of a person. Emotion Based Speaker Recognition has attracted many researchers. Emotions are associated with the variety of feelings and thoughts. An emotion based speaker recognition system, recognizes the person's emotionsbased on pitch, speaking style, intensity, sampling frequency. Mel frequency CepstralCoefficient is the first step in a speaker recognition system. In this paper, we are implementing the gender - based modified MFCC approach to differentiate the individuals. For the classification purpose we have used the K-means algorithm.
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