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Implementation of accent recognition methods subsystem for eLearning systems

机译:电子学习系统的重音识别方法子系统的实现

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The results of the implementation of an external accent recognition system and its integration into massive open online courses platform Moodle are reported. Accent recognition becomes important in foreign languages learning to provide a feedback to a student on a presence of a certain unwanted accent in a foreign language pronunciation. Implementation of several accent recognition methods and their comparison is provided. It is shown that neural networks provide the most reliable recognition given the accented utterances from Wildcat Corpus of Native- and Foreign-Accented English.
机译:报告了实施外部口音识别系统并将其集成到大规模开放式在线课程平台Moodle中的结果。口音识别在外语学习中变得很重要,该学习旨在向学生提供有关外语发音中是否存在某些不想要的口音的反馈。提供了几种口音识别方法的实现及其比较。结果表明,考虑到母语和外国口音英语的Wildcat语料库中的口音,神经网络提供了最可靠的识别。

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