Evaluating the effect of voice activity detection in isolated Yoruba Word Recognition System

This paper discusses and evaluates the effect of voice Activity Detection (VAD) in an isolated Yoruba word ecognition system (IYWRS). The word database used in this paper are collected from 22 speakers by repeating the numbers 1 to 9 three times each. A hybrid configuration of Mel-Frequency Cepstr...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Aibinu, Abiodun Musa, Salami, Momoh Jimoh Eyiomika, Najeeb, Athaur Rahman, Azeez, J. F., Rajin, S. M. Ataul Karim
التنسيق: Conference or Workshop Item
اللغة:English
منشور في: 2011
الموضوعات:
الوصول للمادة أونلاين:http://irep.iium.edu.my/1761/1/Evaluating_the_effect_of_voice_activity_detection_in_isolated_Yoruba_word_recognition_system.pdf
http://irep.iium.edu.my/1761/
http://www.iium.edu.my/ICOM/2011/
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الوصف
الملخص:This paper discusses and evaluates the effect of voice Activity Detection (VAD) in an isolated Yoruba word ecognition system (IYWRS). The word database used in this paper are collected from 22 speakers by repeating the numbers 1 to 9 three times each. A hybrid configuration of Mel-Frequency Cepstral coefficient (MFCC) and Linear Predictive Coding (LPC) have been used to extract the features of the speech samples. Artificial Neural Network algorithms are then used to classify these features. An overall accuracy of about 60% has been achieved from the two proposed feature extraction methods.