Automatic Arabic Pronunciation Scoring for Language Instruction
Automatic articulation scoring makes the computer able to give feedback on the quality of pronunciation and eventually detect some phonemes miss-pronunciation. Computer assisted language learning has evolved from simple interactive software that access the learner’s knowledge in grammar and vocab...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/3188/1/144.pdf http://eprints.um.edu.my/3188/ |
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| Institution: | Universiti Malaya |
| Language: | English |
| Summary: | Automatic articulation scoring makes the computer able to give feedback on the quality of
pronunciation and eventually detect some phonemes miss-pronunciation. Computer assisted
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.
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