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Significance of Differenced EGG Signal as a Spectrum in Phase Difference Computation for the Estimation of Glottal Closure Instants

机译:EGG信号作为频谱在估计声门闭合瞬间的相位差计算中的意义

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摘要

Estimation of glottal closure instants (GCIs) from an electroglottograph (EGG) signal can aid in clinical applications involving the diagnosis and treatment of speech pathologies and can also serve as a ground truth to assess algorithms that estimate GCIs from speech signals. In this regard, the current work proposes a phase-difference-based approach that considers the symmetrized, differenced EGG (DEGG) signal to be the Fourier transform of an arbitrary even-signal, to estimate GCIs from EGG signals. The DEGG signal possesses sharp negative valleys at the GCIs and since the symmetrized DEGG is assumed to be a spectrum, these valleys correspond to zeros that lie outside the unit circle. The angular locations of these zeros, and in turn the locations of GCIs, can be derived from the phase-difference spectrum, since it possesses a value of around at these locations, the derivation of which is elaborated in the paper. The proposed algorithm is compared with the existing time of excitation generator, the high quality time of excitation algorithm, and the singularity in EGG by multiscale analysis algorithm, in terms of the identification, miss, and false alarm rates, and the identification accuracy, on normal and pathological EGG. The proposed algorithm is observed to outperform the rest with an identification rate of 98.28% in normal EGG and 96.90% in pathological EGG.
机译:从电声描记器(EGG)信号估计声门闭合瞬间(GCI)可以帮助临床应用,涉及语音病理学的诊断和治疗,还可以作为评估从语音信号中估计GCI的算法的基础。在这方面,当前的工作提出了一种基于相位差的方法,该方法将对称的差分EGG(DEGG)信号视为任意偶数信号的傅里叶变换,以从EGG信号估计GCI。 DEGG信号在GCI处具有尖锐的负谷,并且由于对称的DEGG被假定为频谱,因此这些谷对应于单位圆之外的零。这些零的角位置以及GCI的位置可以从相差谱中得出,因为它在这些位置处具有大约为的值,其推导过程已在本文中进行了阐述。通过多尺度分析算法,将本文提出的算法与励磁发生器的现有时间,励磁算法的高质量时间以及EGG中的奇异性进行了比较,从识别,漏检,误报率,识别精度等方面进行了比较。正常和病理性EGG。观察到的算法优于其他算法,在正常EGG中的识别率为98.28%,在病理EGG中的识别率为96.90%。

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