Extracting vocal characteristics and calculating vocal synchrony using Praat and R: A tutorial

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-09-29 DOI:10.5964/meth.9375
Désirée Schoenherr, Alisa Shugaley, Franziska Roller, Lukas A. Knitter, Bernhard Strauss, Uwe Altmann
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引用次数: 0

Abstract

In clinical research, the dependence of the results on the methods used is frequently discussed. In research on nonverbal synchrony, human ratings or automated methods do not lead to congruent results. Even when automated methods are used, the choice of the method and parameter settings are important to obtain congruent results. However, these are often insufficiently reported and do not meet the standard of transparency and reproducibility. This tutorial is aimed at researchers who are not familiar with the software Praat and R and shows in detail how to extract acoustic features like fundamental frequency or speech rate from video or audio files in conversations. Furthermore, it is presented how vocal synchrony indices can be calculated from these characteristics to represent how well two interaction partners vocally adapt to each other. All used scripts as well as a minimal example, can be found on the Open Science Framework and Github.

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提取人声特征和计算人声同步使用Praat和R:一个教程
在临床研究中,经常讨论结果对所用方法的依赖性。在非语言同步性的研究中,人类评分或自动化方法不能得出一致的结果。即使使用自动化方法,方法和参数设置的选择对于获得一致的结果也很重要。然而,这些通常报告不足,不符合透明度和可重复性的标准。本教程针对不熟悉Praat和R软件的研究人员,详细介绍了如何从对话中的视频或音频文件中提取基本频率或语音速率等声学特征。此外,本文还介绍了如何从这些特征中计算出声音同步指数,以表示两个互动伙伴在声音上相互适应的程度。所有使用的脚本以及一个最小的例子,都可以在开放科学框架和Github上找到。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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