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Multi-pitch Estimation for Speech Mixture Based on Multi-length Windows Harmonic Model

机译:基于多长度Windows谐波模型的语音混合多音高估计

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Harmonics of two concurrent speech signals may be overlapped in their mixing spectrum from the short time window analysis. We propose a multi-length windows (MLW) method based on harmonic model to estimate the multiple pitches of the single-channel mixed speech. The longest window is used to distinguish all the potential harmonic peaks and initially estimate the other pitch. And the other windows rectify the initial estimation. The advantages of our method include: i) it can obtain more accurate prominent pitch with autocorrelation; ii) it overcomes the low frequency resolution of the traditional harmonic model for estimating the other pitch. The simulation results show that the proposed algorithm outperforms the minimum mean square error (MMSE) method and short window (SW) harmonic method.
机译:根据短时间窗口分析,两个并发语音信号的谐波在其混合频谱中可能会重叠。我们提出了一种基于谐波模型的多长度窗口(MLW)方法,以估计单通道混合语音的多个音高。最长的窗口用于区分所有潜在的谐波峰值,并初步估计其他音调。其他窗口则校正初始估计。我们方法的优点包括:i)可以通过自相关获得更准确的突出音调; ii)克服了传统谐波模型的低频分辨率来估计其他音调。仿真结果表明,该算法优于最小均方误差(MMSE)方法和短窗(SW)谐波方法。

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