Automatic LF-model fitting to the glottal source waveform by extended Kalman filtering

Haoxuan Li, Ronan Scaife, Darragh O'Brien
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引用次数: 4

Abstract

A new method for automatically fitting the Liljencrants-Fant (LF) model to the time domain waveform of the glottal flow derivative is presented in this paper. By applying an extended Kalman filter (EKF) to track the LF-model shape-controlling parameters and dynamically searching for a globally minimal fitting error, the algorithm can accurately fit the LF-model to the inverse filtered glottal flow derivative. Experimental results show that the method has better performance for both synthetic and real speech signals compared to a standard time-domain LF-model fitting algorithm. By offering a new method to estimate the glottal source LF-model parameters, the proposed algorithm can be utilised in many applications.
扩展卡尔曼滤波对声门源波形进行自动低频模型拟合
本文提出了一种将lijencrants - fant (LF)模型与声门流导数的时域波形自动拟合的新方法。该算法采用扩展卡尔曼滤波器(EKF)跟踪声门流模型的形控参数,并动态搜索全局最小拟合误差,将声门流模型精确拟合到反滤波的声门流导数上。实验结果表明,与标准时域lf模型拟合算法相比,该方法对合成语音信号和真实语音信号都具有更好的性能。该算法提供了一种估计声门源低频模型参数的新方法,可用于多种应用场合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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