文章基本信息

标题：Humanising Text-to-Speech Through Emotional Expression in Online Courses
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作者：Garron Hillaire ; Francisco Iniesto ; Bart Rienties 等
期刊名称：Journal of Interactive Media in Education
电子版ISSN：1365-893X
出版年度：2019
卷号：2019
期号：1
页码：12-20
DOI：10.5334/jime.519
出版社：Open University, Knowledge Media Institute
摘要：This paper outlines an innovative approach to evaluating the emotional content of three online courses using the affective computing approach of prosody detection on two different text-to-speech (TTS) voices in conjunction with human raters judging the emotional content of the text. This work intends to establish the potential variation on the emotional delivery of online educational resources through the use of a synthetic voice, which automatically articulates text into audio. Preliminary results from this pilot research suggest that about one out of every three sentences (35%) in a Massive Open Online Course (MOOC) contained emotional text and two existing assistive technology voices had poor emotional alignment when reading this text. Synthetic voices were more likely to be overly negative when considering their expression as compared to the emotional content of the text they are reading, which was most frequently neutral. We also analysed a synthetic voice for which we configured the emotional expression to align with course text, which showed promising improvements.
其他摘要：This paper outlines an innovative approach to evaluating the emotional content of three online courses using the affective computing approach of prosody detection on two different text-to-speech (TTS) voices in conjunction with human raters judging the emotional content of the text. This work intends to establish the potential variation on the emotional delivery of online educational resources through the use of a synthetic voice, which automatically articulates text into audio. Preliminary results from this pilot research suggest that about one out of every three sentences (35%) in a Massive Open Online Course (MOOC) contained emotional text and two existing assistive technology voices had poor emotional alignment when reading this text. Synthetic voices were more likely to be overly negative when considering their expression as compared to the emotional content of the text they are reading, which was most frequently neutral. We also analysed a synthetic voice for which we configured the emotional expression to align with course text, which showed promising improvements.
关键词：emotions; accessibility; MOOCs; Online Learning; text-to-speech
其他关键词：emotions;accessibility;MOOCs;Online Learning;text-to-speech