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Detection of extra pulses in synthesized glottal area waveforms of dysphonic voices

机译:检测语音困难的合成声门区域波形中的多余脉冲

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Background and objectives: The description of production kinematics of dysphonic voices plays an important role in the clinical care of voice disorders. However, high-speed videolaryngoscopy is not routinely used in clinical practice, partly because there is a lack of diagnostic markers that may be obtained from high-speed videos automatically. Aim of the study is to propose and test a procedure that automatically detects extra pulses, which may occur in voiced source signals of pathological voices in addition to cyclic pulses.Material and methods: Glottal area waveforms (GAW) are synthesized and used to test a detector for extra pulses. Regarding synthesis, for each GAW a cyclic pulse train is mixed with an extra pulse train, and additive noise. The cyclic pulse trains are varied across GAWs in terms of fundamental frequency, pulse shape, and modulation noise, i.e., jitter and shimmer. The extra pulse trains are varied across GAWs in terms of the height of the extra pulses, and their rates of occurrence. The energy level of the additive noise is also varied. Regarding detection, first, the fundamental frequency is estimated jointly with the cyclic pulse train waveform, second, the modulation noise is estimated, and finally the extra pulse train waveform is estimated. Two versions of the detector are compared, i.e., one that parameterizes the shapes of the cyclic pulses, and one that uses unparameterized pulse shape estimates. Two corpora are used for testing, i.e., one with 100 GAWs containing random extra pulses, and one with 25 GAWs containing extra pulses in the closed phases of each glottal phase representing subharmonic voices.Results and discussion: With pulse shape parameterization (PSP) a maximum mean accuracy of 88.3% is achieved when detecting random extra pulses. Without PSP, the maximum mean accuracy reduces to 82.9%. Detection performance decreases if the energy level of additive noise is higher than -25 dB with respect to the energy of the cyclic pulse train, and if the irregularity strength exceeds 0.1. For bicyclic, i.e., subharmonic voices, the approach fails without PSP, whereas with PSP, a mean sensitivity of 87.4% is achieved for subharmonic voices.Conclusion: A synthesizer for GAWs containing extra pulses, and a detector for extra pulses are proposed. With PSP, favorable detector performance is observed for not too high levels of additive noise and irregularity strengths. In signals with high noise levels, the detector without PSP outperforms the other one. Detection of extra pulses fails if irregularity strength is large. For subharmonic voices PSP must be used. (C) 2019 The Authors. Published by Elsevier Ltd.
机译:背景与目的:对发音困难的生产运动学的描述在语音障碍的临床护理中起着重要作用。但是,高速视频喉镜检查在临床实践中并不常用,部分原因是缺少可以自动从高速视频中获取的诊断标记。该研究的目的是提出并测试一种程序,该程序可以自动检测除循环脉冲之外还可能出现在病理性语音的语音源信号中的额外脉冲。材料和方法:合成声门区域波形(GAW)并用于测试声门区域波形检测器是否有多余的脉冲。关于合成,对于每个GAW,将循环脉冲序列与额外的脉冲序列和附加噪声混合。整个GAW上的循环脉冲序列在基本频率,脉冲形状和调制噪声(即抖动和闪烁)方面都不同。额外脉冲序列在GAW上根据额外脉冲的高度及其发生率而变化。加性噪声的能级也变化。关于检测,首先,与循环脉冲序列波形一起估计基频,其次,估计调制噪声,最后估计额外的脉冲序列波形。比较了两种类型的检测器,即,一种参数化了循环脉冲的形状,而另一种则使用了未参数化的脉冲形状估计。测试时使用了两种语料库,一种在每个声门相位的封闭相中代表随机谐波的一个带有100个GAW的随机脉冲,另一个在子声相的封闭相中带有一个25个的GAW包含额外的脉冲。结果与讨论:使用脉冲形状参数化(PSP)a检测随机的多余脉冲时,最大平均精度达到88.3%。不使用PSP时,最大平均准确度降低到82.9%。如果加性噪声的能量水平相对于循环脉冲序列的能量高于-25 dB,并且不规则强度超过0.1,检测性能会降低。对于双周期(即亚谐波声音),该方法在没有PSP的情况下会失败,而在PSP下,亚谐波声音的平均灵敏度达到87.4%。结论:提出了一种用于GAW的包含额外脉冲的合成器以及一个用于额外脉冲的检测器。使用PSP时,对于附加噪声和不规则强度水平不太高的情况,可以观察到良好的检测器性能。在具有高噪声水平的信号中,没有PSP的检测器的性能优于另一种。如果不规则强度较大,则多余脉冲的检测将失败。对于亚谐波声音,必须使用PSP。 (C)2019作者。由Elsevier Ltd.发布

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