Abstract
In the language education field, many studies have investigated anxiety associated with learning a second language, noting that anxiety has an adverse effect on the performance of those speaking English as a second language. Accordingly, this study develops an embedded human-emotion-recognition system based on human pulse signals for detecting three human emotions—nervousness, peace, and joy—to help teachers reduce language-learning anxiety of individual learners in a one-to-one synchronous Web-based learning environment. Experimental results indicate that the proposed embedded human-emotion-recognition system is helpful in reducing language-based anxiety and promotes instruction effectiveness in English conversation classes.
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Chen, CM., Hong, CM. (2010). Emotion Recognition and Communication for Reducing Second-Language Speaking Anxiety in a Web-Based One-to-One Synchronous Learning Environment. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13318-3_55
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DOI: https://doi.org/10.1007/978-3-642-13318-3_55
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