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Artificial Companion for Second Language Conversation: Chatbots Support Practice Using Conversation Analysis

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The research described in this book shows that conversation analysis can effectively model dialogue. Specifically, this work shows that the multidisciplinary field of communicative ICALL may greatly benefit from including Conversation Analysis. As a consequence, this research makes several contributions to the related research disciplines, such as conversation analysis, second-language acquisition, computer-mediated communication, artificial intelligence, and dialogue systems.

The book will be of value for researchers and engineers in the areas of computational linguistics, intelligent assistants, and conversational interfaces.

The ability to speak foreign languages has become one of the key competences in the globalised world. People learn foreign languages for professional purposes, with the goal to study abroad or for private reasons. Distance language learning and train ing based on tutoring videos or online exercise books offers a convenient way to integrate language classes into a busy day. Practicing conversation with an artificial agent is seen as a good alternative if a native speaker is not available or not affordable. Computer-Assisted Language Learning (CALL) was expected to facilitate learning and teaching by providing electronic workbooks with automatic evaluation and vo cabulary training. CALL technology extended with Natural Language Processing (NLP) techniques became a new research field called Intelligent Computer-Assisted Language Learning (ICALL). Language technology has been integrated into CALL applications for the purposes of automatised exercise generation (Ai et al., 2015), complex error analysis and automated feedback generation (Amaral, 2011).
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