Phonetically rich and balanced arabic speech corpus: An overview

Lack of spoken and written training data is one o f the main issues encountered by Arabic automatic speech recognition (ASR) researchers. Almost all written and spoken corpora are not readily available to the public and many of them can only be obtained by purchasing from the Linguistic Data Consort...

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Main Authors:	Abushariah, Mohammad A. M., Ainon, Raja N., Zainuddin, Roziati, Khalifa, Othman Omran, Elshafei, Moustafa
Format:	Conference or Workshop Item
Language:	English
Published:	2010
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/5883/ http://irep.iium.edu.my/5883/ http://irep.iium.edu.my/5883/ http://irep.iium.edu.my/5883/1/05556832.pdf

id	iium-5883
recordtype	eprints
spelling	iium-58832011-11-21T22:36:12Z http://irep.iium.edu.my/5883/ Phonetically rich and balanced arabic speech corpus: An overview Abushariah, Mohammad A. M. Ainon, Raja N. Zainuddin, Roziati Khalifa, Othman Omran Elshafei, Moustafa T Technology (General) Lack of spoken and written training data is one o f the main issues encountered by Arabic automatic speech recognition (ASR) researchers. Almost all written and spoken corpora are not readily available to the public and many of them can only be obtained by purchasing from the Linguistic Data Consortium (LDC) or the European Language Resource Association (ELRA). There is more shortage of spoken training data as compared to written training data resulting in a great need for more speech corpora in order to serve different domains of Arabic ASR. The available spoken corpora were mainly collected from broadcast news (radios and televisions), and telephone conversations having certain technical and quality shortcomings. In order to produce a robust speaker-independent continuous automatic Arabic speech recognizer, a set of speech recordings that are rich and balanced is required. The rich characteristic is in the sense that it must contain all the phonemes of Arabic language. It must be balanced in preserving the phonetics distribution of Arabic language too. This set of speech recordings must be based on a proper written set of sentences and phrases created by experts. Therefore, it is crucial to create a high quality written (text) set of the sentences and phrases before recording them. This work adds a new kind of possible speech data for Arabic language based text and speech applications besides other kinds such as broadcast news and telephone conversations. Therefore, this work is an invitation to all Arabic ASR developers and research groups to explore and capitalize. 2010 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/5883/1/05556832.pdf Abushariah, Mohammad A. M. and Ainon, Raja N. and Zainuddin, Roziati and Khalifa, Othman Omran and Elshafei, Moustafa (2010) Phonetically rich and balanced arabic speech corpus: An overview. In: International Conference on Computer and Communication Engineering (ICCCE 2010), 11-13 May 2010, Kuala Lumpur. http://dx.doi.org/10.1109/ICCCE.2010.5556832 doi:10.1109/ICCCE.2010.5556832
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Abushariah, Mohammad A. M. Ainon, Raja N. Zainuddin, Roziati Khalifa, Othman Omran Elshafei, Moustafa Phonetically rich and balanced arabic speech corpus: An overview
description	Lack of spoken and written training data is one o f the main issues encountered by Arabic automatic speech recognition (ASR) researchers. Almost all written and spoken corpora are not readily available to the public and many of them can only be obtained by purchasing from the Linguistic Data Consortium (LDC) or the European Language Resource Association (ELRA). There is more shortage of spoken training data as compared to written training data resulting in a great need for more speech corpora in order to serve different domains of Arabic ASR. The available spoken corpora were mainly collected from broadcast news (radios and televisions), and telephone conversations having certain technical and quality shortcomings. In order to produce a robust speaker-independent continuous automatic Arabic speech recognizer, a set of speech recordings that are rich and balanced is required. The rich characteristic is in the sense that it must contain all the phonemes of Arabic language. It must be balanced in preserving the phonetics distribution of Arabic language too. This set of speech recordings must be based on a proper written set of sentences and phrases created by experts. Therefore, it is crucial to create a high quality written (text) set of the sentences and phrases before recording them. This work adds a new kind of possible speech data for Arabic language based text and speech applications besides other kinds such as broadcast news and telephone conversations. Therefore, this work is an invitation to all Arabic ASR developers and research groups to explore and capitalize.
format	Conference or Workshop Item
author	Abushariah, Mohammad A. M. Ainon, Raja N. Zainuddin, Roziati Khalifa, Othman Omran Elshafei, Moustafa
author_facet	Abushariah, Mohammad A. M. Ainon, Raja N. Zainuddin, Roziati Khalifa, Othman Omran Elshafei, Moustafa
author_sort	Abushariah, Mohammad A. M.
title	Phonetically rich and balanced arabic speech corpus: An overview
title_short	Phonetically rich and balanced arabic speech corpus: An overview
title_full	Phonetically rich and balanced arabic speech corpus: An overview
title_fullStr	Phonetically rich and balanced arabic speech corpus: An overview
title_full_unstemmed	Phonetically rich and balanced arabic speech corpus: An overview
title_sort	phonetically rich and balanced arabic speech corpus: an overview
publishDate	2010
url	http://irep.iium.edu.my/5883/ http://irep.iium.edu.my/5883/ http://irep.iium.edu.my/5883/ http://irep.iium.edu.my/5883/1/05556832.pdf
first_indexed	2023-09-18T20:14:41Z
last_indexed	2023-09-18T20:14:41Z
_version_	1777407708679372800

Phonetically rich and balanced arabic speech corpus: An overview

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