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Design of a text ındependent speaker recognition system

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2017

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Çankaya Meslek Yüksekokulu
Ülkemizin endüstriyel ve hizmete dönük ihtiyaç ve beklentilerini en üst düzeyde karşılayacak, çağdaş, geleceğe umutla bakan, kaliteli bireylerin yetişmesini sağlayan Meslek yüksekokulu olmaktır.

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Abstract

This paper presents the design of a text independent speaker recognition system based on Mel-Frequency Cepstrum Coefficients and Gaussian Mixture Models. HTK speech recognition toolkit is used in the design of speaker models. The system is aimed to use it as a biometric authentication system. The experiments were performed on speech data consist of 134 speakers from YOHO database for different training conditions. The increase of the proposed system performance is observed with the decrease of Equal Error Rate. Experiment results show that the system gives the best recognition performance for Gaussian mixture model with 64 mixtures.

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Speaker Recognition, Voice Recognition, Gaussian Mixture Model, Biometrics, Htk

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Citation

Özaydın, Selma, "Design of a text ındependent speaker recognition system", 2017 International Conference On Electrical And Computing Technologies And Applications (ICECTA), pp.55-59, (2017).

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International Conference on Electrical and Computing Technologies and Applications (ICECTA) -- NOV 21-23, 2017 -- Ras Al Khaimah, U ARAB EMIRATES

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2018-January

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Start Page

55

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59