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

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.

[1]  Árpád Kiss,et al.  Happy Chatbot, Happy User , 2003, IVA.

[2]  Wei Li,et al.  Detecting Mispronunciations of L2 Learners and Providing Corrective Feedback Using Knowledge-Guided and Data-Driven Decision Trees , 2016, INTERSPEECH.

[3]  Maxine Eskenazi,et al.  USING AUTOMATIC SPEECH PROCESSING FOR FOREIGN LANGUAGE PRONUNCIATION TUTORING: SOME ISSUES AND A PROTOTYPE , 1999 .

[4]  Catherine Walter,et al.  A systematic review of CALL in English as a second language: Focus on primary and secondary education , 2011, Language Teaching.

[5]  Kun Li,et al.  Mispronunciation Detection and Diagnosis in L2 English Speech Using Multidistribution Deep Neural Networks , 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[6]  Maxine Eskénazi,et al.  An overview of spoken language technology for education , 2009, Speech Commun..

[7]  Helmer Strik,et al.  Automatic Speech Recognition for second language learning: How and why it actually works , 2003 .

[8]  Steve J. Young,et al.  Phone-level pronunciation scoring and assessment for interactive language learning , 2000, Speech Commun..

[9]  hyang-a Lee An Analysis of Elements to Improve Interactivity in Educational Apps for Smart Learning , 2012 .

[10]  Minhwa Chung,et al.  Mispronunciation Diagnosis of L2 English at Articulatory Level Using Articulatory Goodness-Of-Pronunciation Features , 2017, SLaTE.

[11]  Jiyou Jia,et al.  CSIEC: A computer assisted English learning chatbot based on textual knowledge and reasoning , 2009, Knowl. Based Syst..

[12]  Yoon Kim,et al.  Automatic pronunciation scoring for language instruction , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  Yunkeun Lee,et al.  GenieTutor: A Computer-Assisted Second-Language Learning System Based on Spoken Language Understanding , 2015, Natural Language Dialog Systems and Intelligent Assistants.

[14]  Portia File,et al.  Let's Chat: A conversational dialogue system for second language practice , 2007 .

[15]  Helmer Strik,et al.  Comparing different approaches for automatic pronunciation error detection , 2009, Speech Commun..

[16]  이경아,et al.  The Proposal of Multimedia Contents Method Using Voice Recognition - Focused on the User App Interface for the Children's English - , 2013 .

[17]  Diane Kewley-Port,et al.  Explicit Pronunciation Training Using Automatic Speech Recognition Technology , 2013 .

[18]  Kenji Araki,et al.  Proposal for a Conversational English Tutoring System that Encourages User Engagement , 2011 .