On the comparison of line spectral frequencies and mel-frequency cepstral coefficients using feedforward neural network for language identification

Gunawan, Teddy Surya and Kartiwi, Mira (2018) On the comparison of line spectral frequencies and mel-frequency cepstral coefficients using feedforward neural network for language identification. Indonesian Journal of Electrical Engineering and Computer Science, 10 (1). pp. 168-175. ISSN 2502-4752 E-ISSN 2502-4760

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Abstract

Of the many audio features available, this paper focuses on the comparison of two most popular features, i.e. line spectral frequencies (LSF) and Mel-Frequency Cepstral Coefficients. We trained a feedforward neural network with various hidden layers and number of hidden nodes to identify five different languages, i.e. Arabic, Chinese, English, Korean, and Malay. LSF, MFCC, and combination of both features were extracted as the feature vectors. Systematic experiments have been conducted to find the optimum parameters, i.e. sampling frequency, frame size, model order, and structure of neural network. The recognition rate per frame was converted to recognition rate per audio file using majority voting. On average, the recognition rate for LSF, MFCC, and combination of both features are 96%, 92%, and 96%, respectively. Therefore, LSF is the most suitable features to be utilized for language identification using feedforward neural network classifier.

Item Type:	Article (Journal)
Additional Information:	5588/61795
Uncontrolled Keywords:	Language Identification; LSF; MFCC; Feedforward Neural Network Classifier Recognition Rate
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	13 Feb 2018 11:05
Last Modified:	13 Feb 2018 11:05
URI:	http://irep.iium.edu.my/id/eprint/61795

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