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Comparing Synthesized versus Pre-Recorded Tutor Speech in an Intelligent Tutoring Spoken Dialogue System

机译:在智能辅导口头对话系统中比较合成与预先记录的导师演讲

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We evaluate the impact of tutor voice quality in the context of our intelligent tutoring spoken dialogue system. We first describe two versions of our system which yielded two corpora of human-computer tutoring dialogues: one using a tutor voice pre-recorded by a human, and the other using a low-cost text-to-speech tutor voice. We then discuss the results of two-tailed t-tests comparing student learning gains, system usability, and dialogue efficiency across the two corpora and across corpora subsets. Overall, our results suggest that tutor voice quality may have only a minor impact on these metrics in the context of our tutoring system. We find that tutor voice quality does not impact learning gains, but it may impact usability and efficiency for some corpora subsets.
机译:我们评估导师语音质量在我们智能辅导口语系统背景下的影响。我们首先描述了两个版本的系统,它产生了两种人计算机辅导对话:使用由人类预先录制的导师语音,另一个使用低成本的文本到语音导师语音。然后,我们讨论了两尾T检验的结果,比较了学生学习收益,系统可用性和对话效率,跨越两种CoreDa和Corpora子集。总体而言,我们的结果表明,在我们的辅导系统的背景下,导师语音质量可能只对这些指标产生轻微影响。我们发现导师语音质量不会影响学习收益,但它可能会影响某些语料库的可用性和效率。

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