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( Rokiah Abdullah ),( M. Hariharan ),( Vikneswaran Vijean ),( Farah Nazlia Che Kassim ),( Zulkapli Abdullah ) 한국감성과학회 2017 한국감성과학회 국제학술대회(ICES) Vol.2017 No.-
Malaysia mainly consists of people from three ethnic groups (Malay, Chinese and Indian) and the official and national language of Malaysia is Malay. Malaysian standard English is a form English used and spoken in in Malaysia. Due to the heavy influence of Malay and lack of use of English, Malaysians English accent of Malaysian is not similar to standard English language. So, it is difficult use most commercially available speaker and accent recognition system for Malaysian speaker and accent recognition. Therefore, it is necessary to develop a system to recognize individuals and their accents using the spoken utterances (Malaysian English). Spoken utterances (English digits (0~9) and Malay words) are recorded using the subjects including three ethnic groups (Malay, Chinese and Indian) of Malaysia. Database of speaker and accent are developed using. In this paper, wavelet packet transform based feature extraction method is proposed to extract salient features from the recorded spoken utterances. Support vector machine (SVM) is used to recognize individuals and their accent. The highest accuracy of 92.90% was obtained for speaker identification and 94.89% for accent identification using Malay words whereas the highest accuracy of 91.18% was obtained for speaker identification and 94.17% for accent recognition using Malay digit.