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A Web-Based English Listening System for Learning Different Pronunciations in Various Countries

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Advances in Internet, Data & Web Technologies (EIDWT 2018)

Abstract

The rapid progress of globalization has been increasing our opportunity to have English communication with various people living in different countries. In this study, we focus on ‘local-pronunciation English’, which is English that has characteristics in pronunciation and accent depending on countries and areas, and propose an English listening system for learning different local-pronunciation English in various countries and areas. The feature of our system is that our system can extract countries and areas where English speech is relatively easy to understand to a learner by the sound characteristics, based on the listening learning history of local-pronunciation English. This function allows each learner to learn English listening step by step according to the learner’s listening capability. In this study, we evaluate the feasibility of our system using a Web-based prototype.

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References

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Acknowledgments

We would like to thank all the people who cooperated to record their speech in English for our experiment. Thanks to Ms. Rie Okuda, Ms. Satomi Maki, and other members from International Affair Office, Prof. Tatsuya Inaba, and Lecture Mr. Matsuo from Department of Information and Computer Sciences, we could collect English speech data from Japan. In addition, four students from Chulalongkorn University in Thailand and four students from Electronic Engineering Polytechnic Institute of Surabaya in Indonesia provided their English speech data. We could not have progressed this study without their great help.

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Correspondence to Kohei Kamimura .

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Kamimura, K., Takano, K. (2018). A Web-Based English Listening System for Learning Different Pronunciations in Various Countries. In: Barolli, L., Xhafa, F., Javaid, N., Spaho, E., Kolici, V. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-75928-9_2

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  • DOI: https://doi.org/10.1007/978-3-319-75928-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75927-2

  • Online ISBN: 978-3-319-75928-9

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