Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

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1.60

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Chin-Hwa Kuo1 and Chen-Chung Chi This email address is being protected from spambots. You need JavaScript enabled to view it.1

1Department of Computer Science and Information Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C.


 

Received: March 21, 2013
Accepted: June 28, 2013
Publication Date: December 1, 2013

Download Citation: ||https://doi.org/10.6180/jase.2013.16.4.08  


ABSTRACT


For many EFL learners, reading English articles or listening to music has been a good way to improve their English proficiency. However, it’s not always easy to find the appropriate learning multimedia materials that can satisfy the learners’ interest. The approach proposed in this paper uses a music video recommendation framework which fetches videos from Youtubeto be accessed either via mobile device or web browser. Learners can practice the usage of Verb-Noun collocations by watching the dynamic display of lyrics sentence by sentence, as well as listen to a recommended music video playing at the same time. The proposed system fetches collocation words by calculating mutual information of corpus, choosing music lyrics in the range of appropriate reading difficulty by cluster music lyric based on a particular vocabulary difficulty estimation method, and then providing a practice tool for mobile language learning.


Keywords: Language Learning, Mutual Information, Document Difficulty, Document Readability, Music Recommender System


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