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Recognition of utterances with grammatical mistakes based on optimization of language model towards interactive CALL systems

机译:基于针对交互式CALL系统的语言模型优化的带有语法错误的语音识别

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To realize a voice-interactive CALL system, it is necessary to recognize the learner's utterance correctly including the grammatical mistakes. In this paper, we proposed methods for improving recognition accuracy of speech with grammatical mistakes. The proposed method is based on the method that uses n-gram model trained from sentences that are generated using grammatical error rules. We introduced two improvements to the previous method: one is the utterance discrimination to avoid introducing errors into correct utterances, and the other one is optimization of language model where probability of grammatical mistakes in the generated training text is optimized using the score of utterance discrimination. As a result, we obtained 0.92 point improvement, which is 12% error reduction.
机译:为了实现语音交互的CALL系统,必须正确识别学习者的话语,包括语法错误。本文提出了提高语法错误语音识别精度的方法。所提出的方法基于使用从语法错误规则生成的句子中训练的n元语法模型的方法。我们对之前的方法进行了两项改进:一种是发声识别,以避免将错误引入正确的发声中;另一种是语言模型的优化,其中使用发声识别的分数来优化生成的训练文本中的语法错误概率。结果,我们获得了0.92点的改进,即减少了12%的错误。

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