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Real-time speech segmentation using pitch and convexity jump models: application to variable rate speech coding

机译:使用音高和凸度跳跃模型的实时语音分割:在可变速率语音编码中的应用

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摘要

Convexity jump models are combined with period identification in the time domain to provide an efficient segmentation technique adapted to the needs of coders. The algorithm presented works online, with no training, and is speaker-independent. Structural problems found in previous systems (blank detection spots, long decision delays) have been overcome. Both the simplicity and the generality (information theory basis for the divergence test) allow applications of the automatic online segmentation method in other areas of signal processing.
机译:凸跳模型与时域中的周期标识相结合,以提供一种适用于编码人员需求的有效分割技术。提出的算法可在线运行,无需培训,并且与说话者无关。先前系统中发现的结构性问题(空白检测点,较长的决策延迟)已得到解决。简单性和通用性(差异测试的信息理论基础)都允许将自动在线分割方法应用于信号处理的其他领域。

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