Testing Sphinx’s language model fault-tolerance for the Holy Quran

El Amrani, Mohamed Yassine and Rahman, M.M. Hafizur and Wahiddin, Mohamed Ridza and Shah, Asadullah (2017) Testing Sphinx’s language model fault-tolerance for the Holy Quran. In: 6th International Conference on Information and Communication Technology for the Muslim World (ICT4M 2016), 22nd-24th November 2016, Jakarta, Indonesia.

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Abstract

The Carnegie Mellon University’s (CMU) Sphinx framework is increasingly used for the Arabic speech recognition in general and applied to the Holy Quran in particular. Generating the language model includes a tedious task of preparing the transcriptions for all the data. In this paper, we investigate the fault-tolerance of the automatically generated language model as compared to a corrected and uncorrected transcription with and without silence tagging. This editing addresses the different repetitions and pauses encountered during recitations. Experiments show that the average difference between the lowest and highest Word Error Rate (WER) for each configuration of the number of Senones is 0.6% when using all files for the training and 1.6% when using 80% of the files for training the language model of 17 chapters of the Holy Quran. Results show that the performance of trained models without any correction can be close to when all required rectifications of transcriptions are performed.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	6724/54937
Uncontrolled Keywords:	Automatic speech recognition; Holy Quran recognition; CMU Sphinx 4.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr. M.M. Hafizur Rahman
Date Deposited:	29 Mar 2017 09:31
Last Modified:	04 Feb 2018 14:49
URI:	http://irep.iium.edu.my/id/eprint/54937

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