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Extracting Formulaic Sequences Containing Useful Expressions for Language Learning from Closed Caption TV Corpus
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, , Tokyo University of Foreign Studies, Japan

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Washington, DC, United States Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

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Abstract

This paper describes the details of the formulaic sequences (FS) extracted from closed caption TV (CCTV) data corpus to develop language learning materials of e-learning system. In second language education and applied linguistics, it is a widely acceptance that appropriately using FSs in particular situations and functions contributes to learners’ language comprehension, production, and fluency. In our research, we aim to apply FSs as a language e-learning system’s learning materials. To extract the FSs, we calculated sequences of n words (n-grams) in the corpus, where n is from one to nine. We calculated a total of 3,544,847,579 n-grams from the CCTV corpus of over 655 million words. After a sorting and merging process, we acquired 33,173,413 significant n-grams as FSs candidates. We show the details of the FSs and investigate whether they are useful as language learning materials.

Citation

Mochizuki, H. & Shibano, K. (2016). Extracting Formulaic Sequences Containing Useful Expressions for Language Learning from Closed Caption TV Corpus. In Proceedings of E-Learn: World Conference on E-Learning (pp. 29-37). Washington, DC, United States: Association for the Advancement of Computing in Education (AACE). Retrieved June 28, 2022 from .

© 2016 Association for the Advancement of Computing in Education (AACE)

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