PERFORMING ACCURATE SPEAKER RECOGNITION BY USE OF SVM AND CEPSTRAL FEATURES

Year 2018, Volume: 3 Issue: 2, 16 - 25, 01.01.2019

Zülfikar Aslan , Mehmet Akın

Abstract

The task of performing speaker
recognition over voice recordings is an active research area in the relevant
literature in which many applications has been proposed so far.  In this study, speaker recognition is
performed over cepstral features extracted from raw voice recordings. Some of
the most prominent cepstral feature selection methods, namely, LPC, LPCC, MFCC, PLP and
RASTA-PLP are utilized and their contribution to the performance of the
applied method is investigated. Obtained
features are handled by SVM classification algorithm to finalize the speaker
recognition task. As a result, it is observed
that cepstral feature selection methods such
as LPCC and MFCC combined with SVM classification result
in around 97% accuracy.

Keywords

Speaker recognition, cepstral feature selection, SVM

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