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English sentence pronunciation evaluation using rhythm and intonation

机译:使用节奏和语调评估英语句子的发音

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Rhythm and intonation are important factors in the English sentence pronunciation evaluation. In this paper, the Mel Frequency Cepstrum Coefficient (MFCC) feature and Hidden Markov Model (HMM) algorithm are used to establish a model for speech recognition. Then it makes an evaluation of English sentence pronunciation focusing on rhythm and intonation, and gives feedbacks and recommendations about pronunciation problems to the users based on the expert knowledge. Verified by experiments, the model has a certain precision and reliability. It has applied to a pronunciation evaluation system which can improve users' pronunciation.
机译:节奏和语调是英语句子发音评估中的重要因素。本文利用梅尔频率倒谱系数(MFCC)特征和隐马尔可夫模型(HMM)算法建立语音识别模型。然后以节奏和语调为重点对英语句子发音进行评估,并根据专家知识向用户提供有关发音问题的反馈和建议。经实验验证,该模型具有一定的精度和可靠性。它已被应用到可以改善用户发音的语音评估系统中。

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