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Accurate Estimation of Glottal Closure Instants and Glottal Opening Instants from Electroglottographic Signal Using Variational Mode Decomposition

机译:使用变模分解从电声图信号准确估计声门关闭瞬间和声门打开瞬间

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The objective of the proposed work is to accurately estimate the glottal closure instants (GCIs) and glottal opening instant (GOIs) from electroglottographic (EGG) signals. This work also addresses the issues with existing EGG-based GCI/GOI detection methods. GCIs are the instants at which excitation to the vocal tract is maximum and GOIs, on the other hand, have minimum excitation compared to GCIs. Both these instants occur instantaneously with a fundamental frequency defined for each glottal cycle in a given EGG signal. Accurate detection of these instants from the EGG signal is essential for the performance evaluation of GCIs and GOIs estimated from the speech signal directly. This work proposes a new method for accurate detection of GCIs and GOIs from the EGG signal using variational mode decomposition (VMD) algorithm. The EGG signal has been decomposed into sub-signals using the VMD algorithm. It is shown that VMD captures the center frequency close to the fundamental frequency of the EGG signal through one of its modes. This property of the corresponding mode helps to estimate GCIs and GOIs from the same. Besides, instantaneous pitch frequency is estimated from the obtained GCIs. The proposed method has been evaluated on the CMU-arctic database for GCI/GOI estimation and the Keele pitch extraction reference database for instantaneous pitch frequency estimation. The effectiveness of the proposed method is confirmed by comparison with state-of-the-art methods. Experimental results show that the proposed method has better accuracy and identification rate compared to state-of-the-art methods.
机译:拟议工作的目的是根据电描记图(EGG)信号准确估算声门闭合瞬间(GCI)和声门打开瞬间(GOI)。这项工作还解决了现有的基于EGG的GCI / GOI检测方法的问题。 GCI是对声道的激励最大的时刻,而G​​OI与GCI相比具有最小的激励。在给定的EGG信号中,这两个瞬间都以为每个声门周期定义的基频瞬时发生。从EGG信号中准确检测这些瞬间对于直接从语音信号估计的GCI和GOI的性能评估至关重要。这项工作提出了一种新的方法,可以使用变分模式分解(VMD)算法从EGG信号中准确检测GCI和GOI。使用VMD算法已将EGG信号分解为子信号。结果表明,VMD通过一种模式捕获了接近EGG信号基频的中心频率。相应模式的此属性有助于从中估计GCI和GOI。此外,从获得的GCI估计瞬时音调频率。该方法已在CMU北极数据库进行GCI / GOI估计,并在Keele基音提取参考数据库中进行了瞬时基音频率估计。通过与最先进的方法进行比较,证实了该方法的有效性。实验结果表明,与最新方法相比,该方法具有更高的准确性和识别率。

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