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The Prompt of Lip Shape Modification of Cacology Based on the Speech Evaluation Techniques-a Case of Basic Chinese Learning

机译:基于语音评估技术的朱迹唇形改变的提示 - 基础学习的情况

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In the study, a Chinese learning assisted system based on speech recognition and lip shape image processing is proposed. The mel-frequency cepstral coefficient (MFCC), the pitch contour, and energy curve were adopted as the parameters of voiceprint, speech tone, and magnitude of speech signals, respectively. On the other hand, the height and width of the lip shape were sent into the lip shape analysis. In the scoring stage of speech utterances, the dynamic time warping (DTW) algorithm and probabilistic neural network (PNN) were applied to determine whether the test speech was qualified or not during Chinese learning process. The simulation results indicated that the hybrid of MFCC, pitch contour, and energy curve parameters of speech signal could slightly promote the accuracy of classification-could achieve up to 90%. Finally, the Receiver Operating Characteristic Curve (ROC) was introduced to quantitatively evaluate the sensitivity and specificity of the performance of the proposed algorithm.
机译:在研究中,提出了一种基于语音识别和唇形图像处理的中国学习辅助系统。采用熔融频率谱系码(MFCC),间距轮廓和能量曲线作为声音,语音音和语音信号的大小。另一方面,唇形的高度和宽度被送入唇部形状分析中。在言语话语的评分阶段,应用动态时间翘曲(DTW)算法和概率神经网络(PNN)来确定在中国学习过程中是否有资格。仿真结果表明,语音信号的MFCC,音调轮廓和能量曲线参数的混合可以略微促进分类的准确性 - 可以达到90%。最后,引入了接收器操作特征曲线(ROC)来定量评估所提出的算法性能的灵敏度和特异性。

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