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Second Language Learners' Spoken Discourse: Practice and Corrective Feedback through Automatic Speech Recognition

Second Language Learners' Spoken Discourse: Practice and Corrective Feedback through Automatic Speech Recognition

Catia Cucchiarini, Helmer Strik
Copyright: © 2014 |Pages: 22
ISBN13: 9781466660427|ISBN10: 1466660422|EISBN13: 9781466660434
DOI: 10.4018/978-1-4666-6042-7.ch029
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MLA

Cucchiarini, Catia, and Helmer Strik. "Second Language Learners' Spoken Discourse: Practice and Corrective Feedback through Automatic Speech Recognition." Computational Linguistics: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2014, pp. 618-639. https://doi.org/10.4018/978-1-4666-6042-7.ch029

APA

Cucchiarini, C. & Strik, H. (2014). Second Language Learners' Spoken Discourse: Practice and Corrective Feedback through Automatic Speech Recognition. In I. Management Association (Ed.), Computational Linguistics: Concepts, Methodologies, Tools, and Applications (pp. 618-639). IGI Global. https://doi.org/10.4018/978-1-4666-6042-7.ch029

Chicago

Cucchiarini, Catia, and Helmer Strik. "Second Language Learners' Spoken Discourse: Practice and Corrective Feedback through Automatic Speech Recognition." In Computational Linguistics: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 618-639. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-6042-7.ch029

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Abstract

This chapter examines the use of Automatic Speech Recognition (ASR) technology in the context of Computer Assisted Language Learning (CALL) and language learning and teaching research. A brief introduction to ASR is first provided, to make it clear why and how this technology can be used to the benefit of learning and development in second language (L2) spoken discourse. This is followed by an overview of the state of the art in research on ASR-based CALL. Subsequently, a number of relevant projects on ASR-based CALL conducted at the Centre for Language and Speech Technology of the Radboud University in Nijmegen (the Netherlands) are presented. Possible solutions and recommendations are discussed given the current state of the technology with an explanation of how such systems can be used to the benefit of Discourse Analysis research. The chapter concludes with a discussion of possible perspectives for future research and development.

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