This paper analyzes dysarthric speech datasets from three languages with
different prosodic systems: English, Korean, and Tamil. We inspect 39 acoustic
measurements which reflect three speech dimensions including voice quality,
pronunciation, and prosody. As multilingual analysis, examination on the mean
values of acoustic measurements by intelligibility levels is conducted.
Further, automatic intelligibility classification is performed to scrutinize
the optimal feature set by languages. Analyses suggest pronunciation features,
such as Percentage of Correct Consonants, Percentage of Correct Vowels, and
Percentage of Correct Phonemes to be language-independent measurements. Voice
quality and prosody features, however, generally present different aspects by
languages. Experimental results additionally show that different speech
dimension play a greater role for different languages: prosody for English,
pronunciation for Korean, both prosody and pronunciation for Tamil. This paper
contributes to speech pathology in that it differentiates between
language-independent and language-dependent measurements in intelligibility
classification for English, Korean, and Tamil dysarthric speech.

本文分析了来自英语、韩语和泰米尔语三种具有不同韵律系统的语言的语音障碍者讲话数据集，检查反映语音质量、发音和韵律三个讲话维度的 39 个声学测量标准，提出在了解说话的可懂水平的平均声学测量值的基础上进行多语种分析，并进行自动可懂性分类以研究最佳功能集。分析表明发音特征是语言无关的测量标准，如音素正确百分比、辅音正确百分比和元音正确百分比，而声音质量和韵律特征通常呈现不同的语言特征。实验结果进一步表明，不同的语音维度在不同的语言中发挥更大的作用：英语的韵律，韩语的发音，泰米尔语的韵律和发音。这篇论文为语音病理学做出了贡献，因为它区分了英语、韩语和泰米尔语的语音障碍者可懂性分类中语言无关和语言相关的测量标准。