Automatic Arabic pronunciation scoring for language instruction

Dahan, Hassan and Hussin, Abdul and Razak, Zaidi and Odelha, Mourad (2011) Automatic Arabic pronunciation scoring for language instruction. In: 3rd International Conference on Education and New Learning Technologies (EDULEARN11), 4-6 July 2011, Barcelona, Spain.

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Automatic articulation scoring makes the computer able to give feedback on the quality of pronunciation and eventually detect some phonemes miss-pronunciation. Computerassisted language learning has evolved from simple interactive software that access the learner’s knowledge in grammar and vocabulary to more advanced systems that accept speech input as a result of the recent development of speech recognition[1]. Therefore many computer based self teaching systems have been developed for several languages such English, Deutsch and Chinese, however for Arabic; the research is still in its beginning. This study is part of the “Arabic Pronunciation improvement system for Malaysian Teachers of Arabic language” project which aimed at developing computer based systems for standards Arabic language instruction for Malaysian teachers of Arabic language. The system aims to help teachers to learn Arabic language quickly by focusing on the listening and speaking comprehension (receptive skills) to improve their pronunciation[2,3]. In this paper we addressed the problem of giving marks for Arabic pronunciation by using a Automatic Speech Recognizer (ASR) based on Hidden Markov Models (HMM), thus our approach to pronunciation scoring is based on the HMM log-likelihood probability.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Arabic Pronunciation scoring; Hidden Markov Models (HMMs); Log-Likelihood probability; Baum Welch algorithm; Viterbi algorithm
Subjects: L Education > L Education (General)
P Language and Literature > PJ Semitic
Divisions: Faculty of Computer Science & Information Technology
Faculty of Education
Depositing User: Mr. Mohd Samsul Ismail
Date Deposited: 18 Feb 2015 01:24
Last Modified: 14 Nov 2019 07:44

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