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使用音高高度和音高强度来表征1型、2型和3型语音信号。

Using Pitch Height and Pitch Strength to Characterize Type 1, 2, and 3 Voice Signals.

作者信息

Anand Supraja, Kopf Lisa M, Shrivastav Rahul, Eddins David A

机构信息

Department of Communication Sciences and Disorders, University of South Florida, Tampa, Florida.

Department of Communication Sciences and Disorders, University of Northern Iowa, Cedar Falls, Iowa.

出版信息

J Voice. 2021 Mar;35(2):181-193. doi: 10.1016/j.jvoice.2019.08.006. Epub 2019 Sep 5.

Abstract

OBJECTIVE

Classifying dysphonic voices as type 1, 2, and 3 signals based on their periodicity enables researchers to determine the validity of acoustic measures derived from them. Existing methods of signal typing are commonly performed by listening to the voice sample and visualizing them on narrow-band spectrograms that require training, time, and are subjective in nature. The current study investigated pitch-based metrics (pitch height and pitch strength) as correlates to characterizing voice signal types. The computational estimates were validated with perceptual judgments of pitch height and pitch strength.

METHODS

Pitch height and pitch strength were estimated from Auditory-Sawtooth Waveform Inspired Pitch Estimator Prime algorithm for 30 dysphonic voice segments (10 per type). Ten listeners evaluated pitch height through a single-variable matching task and pitch strength through an anchored magnitude estimation task. One way analyses of variance were used to determine the effects of signal type on pitch height and pitch strength estimates. Relationship between computational and perceptual estimates was evaluated using correlation coefficients and their significance.

RESULTS

There was a significant difference between signal types in both computational and perceptual pitch strength estimates. Periodic type 1 signals had greater pitch strength compared to type 2 and 3 signals. Auditory-Sawtooth Waveform Inspired Pitch Estimator Prime produced robust computational estimates of pitch height even in type 3 signals when compared to other acoustic software. Listeners were able to reliably judge pitch height in type 2 and 3 signals despite their lack of a clear fundamental frequency.

CONCLUSIONS

Pitch height and pitch strength can be measured in all dysphonic voices irrespective of signal periodicity.

摘要

目的

根据周期性将发声障碍的声音分类为1型、2型和3型信号,这使研究人员能够确定从这些声音中得出的声学测量方法的有效性。现有的信号分类方法通常是通过听取语音样本并在需要训练、耗时且本质上主观的窄带声谱图上进行可视化来完成的。本研究调查了基于音高的指标(音高高度和音高强度)与语音信号类型特征之间的相关性。通过对音高高度和音高强度的感知判断对计算估计进行了验证。

方法

使用听觉锯齿波形启发的音高估计器Prime算法对30个发声障碍语音片段(每种类型10个)的音高高度和音高强度进行估计。10名听众通过单变量匹配任务评估音高高度,通过锚定量级估计任务评估音高强度。使用单因素方差分析来确定信号类型对音高高度和音高强度估计的影响。使用相关系数及其显著性评估计算估计与感知估计之间的关系。

结果

在计算和感知的音高强度估计中,信号类型之间存在显著差异。与2型和3型信号相比,周期性1型信号具有更高的音高强度。与其他声学软件相比,即使在3型信号中,听觉锯齿波形启发的音高估计器Prime也能对音高高度进行可靠的计算估计。尽管2型和3型信号缺乏清晰的基频,但听众仍能够可靠地判断其音高高度。

结论

无论信号的周期性如何,所有发声障碍的声音都可以测量音高高度和音高强度。

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