Towards using CMU sphinx tools for the Holy Quran recitation verification
The use of the Automatic Speech Recognition (ASR) technology is being used in many different applications that help simplify the interaction with a wider range of devices. This paper investigates the use of a simplified set of phonemes in an ASR system applied to Holy Quran. The Carnegie Mellon Univ...
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iium-519122016-09-22T08:35:35Z http://irep.iium.edu.my/51912/ Towards using CMU sphinx tools for the Holy Quran recitation verification El Amrani, Mohamed Yassine Rahman, M.M. Hafizur Wahiddin, Mohamed Ridza Shah, Asadullah TK Electrical engineering. Electronics Nuclear engineering TK7885 Computer engineering The use of the Automatic Speech Recognition (ASR) technology is being used in many different applications that help simplify the interaction with a wider range of devices. This paper investigates the use of a simplified set of phonemes in an ASR system applied to Holy Quran. The Carnegie Mellon University Sphinx 4 tools were used to train and evaluate a language model on Holy Quran recitations that are widely available online. The building of the language model was done using a simplified list of phonemes instead of the mainly used Romanized in order to simplify the process of training the acoustic model. In this paper, the experiments resulted in Word Error Rates (WER) as low as 1.5% even with a very small set of audio files used during the training phase. UniTECH 2016-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/51912/1/IJASAT_Published.pdf El Amrani, Mohamed Yassine and Rahman, M.M. Hafizur and Wahiddin, Mohamed Ridza and Shah, Asadullah (2016) Towards using CMU sphinx tools for the Holy Quran recitation verification. International Journal on Islamic Applications in Computer Science And Technology (IJASAT), 4 (2). pp. 10-15. ISSN 2289-4012 E-ISSN 2289-4012 http://www.sign-ific-ance.co.uk/index.php/IJASAT/article/view/1424 |
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TK Electrical engineering. Electronics Nuclear engineering TK7885 Computer engineering |
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TK Electrical engineering. Electronics Nuclear engineering TK7885 Computer engineering El Amrani, Mohamed Yassine Rahman, M.M. Hafizur Wahiddin, Mohamed Ridza Shah, Asadullah Towards using CMU sphinx tools for the Holy Quran recitation verification |
description |
The use of the Automatic Speech Recognition (ASR) technology is being used in many different applications that help simplify the interaction with a wider range of devices. This paper investigates the use of a simplified set of phonemes in an ASR system applied to Holy Quran. The Carnegie Mellon University Sphinx 4 tools were used to train and evaluate a language model on Holy Quran recitations that are widely available online. The building of the language model was done using a simplified list of phonemes instead of the mainly used Romanized in order to simplify the process of training the acoustic model. In this paper, the experiments resulted in Word Error Rates (WER) as low as 1.5% even with a very small set of audio files used during the training phase. |
format |
Article |
author |
El Amrani, Mohamed Yassine Rahman, M.M. Hafizur Wahiddin, Mohamed Ridza Shah, Asadullah |
author_facet |
El Amrani, Mohamed Yassine Rahman, M.M. Hafizur Wahiddin, Mohamed Ridza Shah, Asadullah |
author_sort |
El Amrani, Mohamed Yassine |
title |
Towards using CMU sphinx tools for the Holy Quran recitation verification |
title_short |
Towards using CMU sphinx tools for the Holy Quran recitation verification |
title_full |
Towards using CMU sphinx tools for the Holy Quran recitation verification |
title_fullStr |
Towards using CMU sphinx tools for the Holy Quran recitation verification |
title_full_unstemmed |
Towards using CMU sphinx tools for the Holy Quran recitation verification |
title_sort |
towards using cmu sphinx tools for the holy quran recitation verification |
publisher |
UniTECH |
publishDate |
2016 |
url |
http://irep.iium.edu.my/51912/ http://irep.iium.edu.my/51912/ http://irep.iium.edu.my/51912/1/IJASAT_Published.pdf |
first_indexed |
2023-09-18T21:13:36Z |
last_indexed |
2023-09-18T21:13:36Z |
_version_ |
1777411415302209536 |