A Novel Approach in Text-Independent Speaker Recognition in Noisy Environment

Subject Areas : Signal and systems processing

Nona  Heydari Esfahani ¹ (MSc – Persian Foolal Company, Isfahan)
Hamid  Mahmoodian ² (Assistant Professor - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University)

Received: 2013-07-23 Accepted : 2014-05-22 Published : 2014-12-01

Keywords: Shannon Entropy, MLP, Speaker identification, MFCC coefficients, pitch ferequency, formants,

Abstract :

In this paper, robust text-independent speaker recognition is taken into consideration. The proposed method performs on manual silence-removed utterances that are segmented into smaller speech units containing few phones and at least one vowel. The segments are basic units for long-term feature extraction. Sub-band entropy is directly extracted in each segment. A robust vowel detection method is then applied on each segment to separate a high energy vowel that is used as unit for pitch frequency and formant extraction. By applying a clustering technique, extracted short-term features namely MFCC coefficients are combined with long term features. Experiments using MLP classifier show that the average speaker accuracy recognition rate is 97.33% for clean speech and 61.33% in noisy environment for -2db SNR, that shows improvement compared to other conventional methods.

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