Browse > Article
http://dx.doi.org/10.9728/dcs.2018.19.4.621

A Study on the Utilization of Speech Recognition Technology in Foreign Language Learning Applications - Focusing on English and French Speech -  

Kim, Sunhee (Clova, Naver Corporation)
Jung, Hyunhoon (Graduate School of Convergence Science and Technology, Seoul National University)
Publication Information
Journal of Digital Contents Society / v.19, no.4, 2018 , pp. 621-630 More about this Journal
Abstract
This paper presents a case study on foreign language learning applications based on the speech recognition technology, aiming to grasp their current status and limitations of the technology applied to the foreign language speaking education, especially for English and French. As a result of examining the characteristics of the selected English and French applications by drawing on speech learning, it is shown that the use of speech recognition technology has the advantage of creating a speaking practice environment and giving feedback. However, in the case of feedback, there is a lack of appropriate calibration feedback which can help learners correct errors by themselves.
Keywords
English; French; Language learning; Pronunciation assessment; Speech recognition;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Eskenazi, M. (1999). Using automatic speech processing for foreign language pronunciation tutoring: Some issues and a prototype. Language Learning & Technology, Volume 2, Number 2, 62-76.
2 Li, K., Qian, X., & Meng, H. (2017). Mispronunciation detection and diagnosis in l2 English speech using multidistribution deep neural networks. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25(1), 193-207.   DOI
3 Li, W., Li, K., Siniscalchi, S. M., Chen, N. F., & Lee, C. H. (2016). Detecting Mispronunciations of L2 Learners and Providing Corrective Feedback Using Knowledge-Guided and Data-Driven Decision Trees. In Interspeech, 3127-3131.
4 Park E. Y. & K. A Lee (2013). The proposal of multimedia contents method using voice recognition - Focused on the user app interface for the children's English. A journal of Brand Design Association of Korea, 24.
5 Oh, E. Y. (2017). Developmental research on an interactive application through speech recognition technology for foreign language speaking practice. Doctoral dissertation, The graduate school, Seoul National University.
6 Lee, H. A & J. Youn (2012). An analysis of elements to improve interactivity in educational apps for smart learning. Korea Science & Art Forum 10, 2012.07, 143-154
7 Kwon, O. W., Lee, K., Roh, Y. H., Huang, J. X., Choi, S. K., Kim, Y. K., ... & Chung, E. (2015). GenieTutor: A Computer-Assisted Second-Language Learning System Based on Spoken Language Understanding. In Natural Language Dialog Systems and Intelligent Assistants (pp. 257-262). Springer, Cham.
8 Jang, B.-Y. (2015), Etude sur l'Application de Smart-Learning pour l'enseignement d'une langue etrangere. The Journal of Linguistic Science 71, 377-396.
9 Dalby, J., & Kewley-Port, D. (1999). Explicit pronunciation training using automatic speech recognition technology. CALICO journal, 425-445.
10 Eskenazi, M. (2009). An overview of spoken language technology for education. Speech Communication, 51(10), 832-844.   DOI
11 Lee,Y. K. (2013). Conversational voice interface technology and services. IEEK Summer Conference 2013, 1847-1849
12 Neri,A., Cucchiarini, C.,&Strik W. (2003). Automatic speech recognition for second language learning: How and why is actually works. In Proceedings of the 15th international Conference on Phonetic Sciences, 1157-1160.
13 Franco, H., Neumeyer, L., Kim, Y., & Ronen, O. (1997). Automatic pronunciation scoring for language instruction. In IEEE International Conference on Acoustics, Speech, and Signal Processing, 1997. Vol. 2, 1471-1474.
14 Witt, S. M., & Young, S. J. (2000). Phone-level pronunciation scoring and assessment for interactive language learning. Speech communication, 30(2-3), 95-108.   DOI
15 Strik, H., Truong, K., De Wet, F., & Cucchiarini, C. (2009). Comparing different approaches for automatic pronunciation error detection. Speech communication, 51(10), 845-852.   DOI
16 Jia, J.(2009). CSIEC: A computer assisted English learning chatbot based on textual knowledge and reasoning. Knowledge-Based Systems, 22(4), 249-255.   DOI
17 Ryu, H., & Chung, M. (2017). Mispronunciation Diagnosis of L2 English at Articulatory Level Using Articulatory Goodness-Of-Pronunciation Features. In Proc. 7th ISCA Workshop on Speech and Language Technology in Education 65-70.
18 Tatai G., Csordas A., Kiss A., Szalo A., and Laufer L. (2003). Happy chatbot, happy user. Intelligent Virtual Agents, vol. 2792, 5-12.
19 Stewart I., File P. (2007). Let's chat: A conversational dialogue system for second language practice. Computer Assisted Language Learning, 20, 97.116.   DOI
20 Macaro, E., Handley, Z., & Walter, C. (2012). A systematic review of CALL in English as a second language: Focus on primary and secondary education. Language Teaching, 45(1), 1-43.   DOI
21 Mazur, M., Rzepka, R., & Araki, K. (2011). Proposal for a conversational English tutoring system that encourages user engagement. In Proceedings of the 19th International Conference on Computers in Education (pp. 10-12).
22 Yun-Roger, Y. (2012). Le Smartphone dans un cours de langue etrangere - retour d'experience d'un cours de francais oral a l'Universite en Coree, Revue d'Etudes francaises 78, 2012.5, 405-431
23 Kim, H.-Z. (2014). A propos de la possibilite sur l'apprentissage du francais mettant en oeuvre des appareils mobiles, Societe Coreenne d'Enseignement de Langue et Litterature Francaises 45, 43-73.