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The effectiveness of computer-based speech corrective feedback for improving segmental quality in L2 Dutch

机译:基于计算机的语音校正反馈对提高二语荷兰语段质量的有效性

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Although the success of automatic speech recognition (ASR)-based Computer Assisted Pronunciation Training (CAPT) systems is increasing, little is known about the pedagogical effectiveness of these systems. This is particularly regrettable because ASR technology still suffers from limitations that may result in the provision of erroneous feedback, possibly leading to learning breakdowns. To study the effectiveness of ASR-based feedback for improving pronunciation, we developed and tested a CAPT system providing automatic feedback on Dutch phonemes that are problematic for adult learners of Dutch. Thirty immigrants who were studying Dutch were assigned to three groups using either the ASR-based CAPT system with automatic feedback, a CAPT system without feedback, or no CAPT system. Pronunciation quality was assessed for each participant before and after the training by human experts who evaluated overall segmental quality and the quality of the phonemes addressed in the training. The participants' impressions of the CAPT system used were also studied through anonymous questionnaires. The results on global segmental quality show that the group receiving ASR-based feedback made the largest mean improvement, but the groups' mean improvements did not differ significantly. The group receiving ASR-based feedback showed a significantly larger improvement than the no-feedback group in the segmental quality of the problematic phonemes targeted.
机译:尽管基于自动语音识别(ASR)的计算机辅助语音训练(CAPT)系统的成功正在增加,但是对于这些系统的教学效果知之甚少。这尤其令人遗憾,因为ASR技术仍然受限制,可能会导致提供错误的反馈,从而导致学习失败。为了研究基于ASR的反馈对改善语音的有效性,我们开发并测试了CAPT系统,该系统提供了对荷兰成语学习者有问题的荷兰音素的自动反馈。使用基于ASR的具有自动反馈功能的CAPT系统,无反馈的CAPT系统或无CAPT系统,将30名正在研究荷兰语的移民分为三类。在培训之前和之后,由人类专家对每个参与者的语音质量进行评估,他们会评估整体片段质量和培训中解决的音素质量。还通过匿名调查表研究了参与者对使用的CAPT系统的印象。全球细分质量的结果显示,接受基于ASR的反馈的小组的平均改善幅度最大,但是小组的平均改善并没有显着差异。接收到基于ASR的反馈的组在有问题的音素的细分质量上比无反馈组显着提高。

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