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Research on English pronunciation training based on intelligent speech recognition

机译:基于智能语音识别的英语发音训练研究

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摘要

When learning English, Chinese students tend to spend a lot of time in practicing reading and writing skills, while neglecting their ability to speak English. This study presented a speech recognition-based intelligent spoken English pronunciation training system which took Mel Frequency Cepstral Coefficients as the characteristic parameter of speech signal and introduced deep neural network algorithm to improve the accuracy of speech recognition. Taking tone, speech speed and intonation as the evaluation criteria, a simulation experiment of artificial evaluation and machine evaluation was carried out. The results demonstrated that deep neural network had high speech recognition rate, and the three evaluation criteria were reliable, which provides a reference for the development of spoken English learning system.
机译:在学习英语时,中国学生往往会花大量时间练习阅读和写作技巧,而忽略了他们的英语口语能力。本研究提出了一种基于语音识别的智能英语口语训练系统,该系统以梅尔频率倒谱系数为语音信号的特征参数,并引入深度神经网络算法来提高语音识别的准确性。以音调,语速和语调为评价标准,进行了人工评价和机器评价的仿真实验。结果表明,深度神经网络具有较高的语音识别率,三个评价指标均可靠,为英语口语学习系统的发展提供了参考。

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