The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students

This project is to examine the accuracy of using existing speech recognition engine in interactive dialog system for English as second language (ESL) Malaysian primary school student in literacy education. Students are interested to learn literacy using computer that encompasses spoken dialog as it...

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Main Author:	Hasliemelia, Abu Hassan @ Aziz
Format:	Thesis
Language:	eng eng
Published:	2012
Subjects:	LB1501 Primary Education
Online Access:	https://etd.uum.edu.my/3293/1/HASLIEMELIA_ABU_HASSAN_%40_AZIZ.pdf https://etd.uum.edu.my/3293/3/HASLIEMELIA_ABU_HASSAN_%2540_AZIZ.pdf
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id	my-uum-etd.3293
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Mat Aji @ Alon, Zahurin Husni, Husniza
topic	LB1501 Primary Education LB1501 Primary Education
spellingShingle	LB1501 Primary Education LB1501 Primary Education Hasliemelia, Abu Hassan @ Aziz The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students
description	This project is to examine the accuracy of using existing speech recognition engine in interactive dialog system for English as second language (ESL) Malaysian primary school student in literacy education. Students are interested to learn literacy using computer that encompasses spoken dialog as it motivates students to be more confidence in reading and pronunciation without depending solely on teachers. This computer assisted learning will improve student’s oral reading ability by using the speech recognition in IDS. By using the system students are able to learn, to read and pronounce a word correctly independently without seeking help from teachers. This study is conducted at Sungai Berembang Primary School involving all 16 female and 18 male standard 2 students aged 8 years old. These students possess various reading pronunciation, abilities, and experience in English language with Malay language as their first language. The main objective of this studyis to examine the accuracy of using an existing speech recognition engine for ESL Malaysian students in literacy education. The specific objectives of this study are to identify requirement and evaluate speech recognition based dialog system for reading accuracy. This kind of speech recognition technology is aiming to provide teacher-similar tutoring ability in children’s phonemic awareness, vocabulary building, word comprehension, and fluent reading.This method has five stages. This method enables to construct a framework. Develop system architecture then analyze and design the system. It also builds the prototype for the system upon the system implementation which will be used in this study is the System Development Research Method.Lastly its observe, test the system and the results of the study and implementation of IDS students found 85% of this has helped the English language after using this system.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Hasliemelia, Abu Hassan @ Aziz
author_facet	Hasliemelia, Abu Hassan @ Aziz
author_sort	Hasliemelia, Abu Hassan @ Aziz
title	The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students
title_short	The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students
title_full	The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students
title_fullStr	The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students
title_full_unstemmed	The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students
title_sort	pronunciation accuracy of interactive dialog system for malaysian primary school students
granting_institution	Universiti Utara Malaysia
granting_department	College of Arts and Sciences (CAS)
publishDate	2012
url	https://etd.uum.edu.my/3293/1/HASLIEMELIA_ABU_HASSAN_%40_AZIZ.pdf https://etd.uum.edu.my/3293/3/HASLIEMELIA_ABU_HASSAN_%2540_AZIZ.pdf
_version_	1747827539945979904
spelling	my-uum-etd.32932016-04-27T01:47:03Z The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students 2012 Hasliemelia, Abu Hassan @ Aziz Mat Aji @ Alon, Zahurin Husni, Husniza College of Arts and Sciences (CAS) College of Art and Sciences LB1501 Primary Education QA75 Electronic computers. Computer science This project is to examine the accuracy of using existing speech recognition engine in interactive dialog system for English as second language (ESL) Malaysian primary school student in literacy education. Students are interested to learn literacy using computer that encompasses spoken dialog as it motivates students to be more confidence in reading and pronunciation without depending solely on teachers. This computer assisted learning will improve student’s oral reading ability by using the speech recognition in IDS. By using the system students are able to learn, to read and pronounce a word correctly independently without seeking help from teachers. This study is conducted at Sungai Berembang Primary School involving all 16 female and 18 male standard 2 students aged 8 years old. These students possess various reading pronunciation, abilities, and experience in English language with Malay language as their first language. The main objective of this studyis to examine the accuracy of using an existing speech recognition engine for ESL Malaysian students in literacy education. The specific objectives of this study are to identify requirement and evaluate speech recognition based dialog system for reading accuracy. This kind of speech recognition technology is aiming to provide teacher-similar tutoring ability in children’s phonemic awareness, vocabulary building, word comprehension, and fluent reading.This method has five stages. This method enables to construct a framework. Develop system architecture then analyze and design the system. It also builds the prototype for the system upon the system implementation which will be used in this study is the System Development Research Method.Lastly its observe, test the system and the results of the study and implementation of IDS students found 85% of this has helped the English language after using this system. 2012 Thesis https://etd.uum.edu.my/3293/ https://etd.uum.edu.my/3293/1/HASLIEMELIA_ABU_HASSAN_%40_AZIZ.pdf text eng validuser https://etd.uum.edu.my/3293/3/HASLIEMELIA_ABU_HASSAN_%2540_AZIZ.pdf text eng public masters masters Universiti Utara Malaysia Aist,G. (1998). Expanding A Time-Sensitive Conversational Architecture For Turn-Taking To Handle Content-Driven Interruption. Allen,L., Abella,A., Alonso,T., & Jeremy,H. (2002). Automated natural spoken dialog. Avison,D., & Fitzgerald,G. (2003). Information systems development: methodologies, techniques and tools: McGraw-Hill. Broady,C. (2009). Congolese Culture and the French and Kikongo Languages:. Congolese Culture and the French and Kikongo Languages: A Linguistic Analysis Jenna Zent EDU 583 Burgt,S.P.v.d., Andernach,T., Kloosterman,H., Bos,R., & Nijhol,A. (1996). Building Dialogue Systems that Sell (pp.41-46). New Brunswick: Proceedings Natural Language Processing and Industrial Applications. Carlson,R., Edlund,J., Heldner,M., Hjalmarsson,A., House,D., Skantze,G., et al. (2006). Towards human-like behavior in spoken dialog systems. Choi,E. (2004). Noise robust front-end for ASR using spectral subtraction, spectral flooring and cumulative distribution mapping. Cook,S. (2003). Speech Recognition HOWTO. Home Page. Dahl,M.,& Claesson,I. (1999). Acoustic noise and echo cancelling with microphone array. Vehicular Technology, IEEE Transactions on, 48(5), 1518-1526. Di Fabbrizio,G., Tur,G., & Hakkani-Tür,D. (2004). Boot-strapping spoken dialog systems with data reuse. Eckert, Penelope. 2000. Linguistic variation as social practice. Oxford: Blackwell. http://www.stanford.edu/~eckert/csofp.html Fernández,R., Corradini,A., Schlangen,D., & Stede,M. (2007). Towards reducing and managing uncertainty in spoken dialogue systems. Hieronymus,J., & Dowding,J. (2004).Clarissa spoken dialogue system for procedure reading and navigation: Citeseer. J.Hirschberg, J.Liscombe and J.Venditti, (2003). “Experiments in Emotional Speech,” Proceedings of the ISCA and IEEE Workshop on Spontaneous Speech Processing and Recognition, Tokyo.http://www.cs.columbia.edu/~julia/files/cv.pdf Kamm,C. (1995). User interfaces for voice applications. Proceedings of the National Academy of Sciences, 92(22), 10031. Kementerian Pelajaran Malaysia (2011), Huraian Sukatan Pelajaran Tahun 2 KSSR Kim,L.S. (2006). Masking: Maneuvers of Skilled ESL Speakers in Postcolonial Societies. English in Southeast Asia: prospects, perspectives, and possibilities, 191. Lee S.K. (2001). A qualitative study of the impact of the English language on the construction of the sociocultural identities of ESL speakers.Unpublished doctoral dissertation , College of Education, University of Houston, USA. Lee S.K. (2003). Multiple identities in a multicultural world: A Malaysian perspective. Journal of Language, Identity and Education 2(3), 137-158. Lee S.K. (2005). What Price English? Identity constructions and identity conflicts in the acquisition of English. In Lee Su Kim, Thang Siew Ming and Kesumawati Abu Bakar. Language and nationhood: New contexts, new realities. SoLL’s UKM: Bangi. Lee S.K. (2006). Masking: Maneuvers of Skilled ESL Speakers in Postcolonial Societies. In Azirah Hashim and Norizah Hassan (Eds.) English in South East Asia: Prospects, perspectives and possibilities. K. Lumpur: University of Malaya Press. Lee S.K. (2008). Masks of identity: Negotiating multiple identities. Paper presented at JALT International Conference, Tokyo, Japan. Lee S.K, Thang Siew Ming & Lee King Siong (2007). Border crossings: Moving across languages and cultural frameworks. Kuala Lumpur: Pelanduk Publications. Lee,S.K., Lee,K.S., & Wong,F.F. (2010). The English Language And Its Impact On Identities Of Multilingual Malaysian Undergraduates. Levin,E., Pieraccini,R., & Eckert,W. (2000). A stochastic model of human-machine interaction for learning dialog strategies. Speech and Audio Processing, IEEE Transactions on, 8(1), 11-23. Littlefield,J., & Broughton,M. (2005). Dual-Type Automatic Speech Recogniser Designs for Spoken Dialogue Systems. Musa,N.C., Koo,Y.L., & Azman,H. (2012). Exploring English language learning and teaching in Malaysia. GEMA: Online Journal of Language Studies, 12(1), 35-51. Murugesan,V. (2003). Malaysia promotes excellence in English. ESL MAGAZINE. Natarajan,P., Prasad,R., Suhm,B., & McCarthy,D. (2002). Speech-enabled natural language call routing: BBN Call Director. Nunamaker Jr,J.F., & Chen,M. (1990). Systems development in information systems research. Pietquin,O., & Renals,S. (2002). ASR system modeling for automatic evaluation and optimization of dialogue systems. Plannerer Bernd,(2005) Munich, Germany. An Introduction to Speech Recognition. http://www.speech-recognition.de/pdf/ introSR.pdf Raux,A. (2008). Flexible turn-taking for spoken dialogue systems. PhD Thesis, Carnegie Mellon University. Sukatan Pelajaran Bahasa Inggeris KSSRTahun 2 (2011), KPM www.moe.gov.my/bpk/sp_hsp/bi/kssr/sp_bi_kbsr.pdf] Tomko,S. (2005). Improving user interaction with spoken dialog systems via shaping. Vaishnavi,V., & Kuechler,W. (2007). Design research in information systems. wwwisworldorg, 22(2), 1-16. Witt& Young, (1997) Interactive pronunciation training. citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.24.rep

The Pronunciation Accuracy of Interactive Dialog System for Malaysian Primary School Students

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