Phonetics is the scientific field concerned with the study of how speech is produced, heard, and perceived. It abounds with data, such as acoustic speech recordings, neuroimaging data, or articulatory data. In this article, we provide an introduction to different areas of phonetics (acoustic phonetics, sociophonetics, speech perception, articulatory phonetics, speech inversion, sound change, and speech technology), an overview of the statistical methods for analyzing their data, and an introduction to the signal processing methods commonly applied to speech recordings. A major transition in the statistical modeling of phonetic data has been the shift from fixed effects to random effects regression models, the modeling of curve data (for instance, via generalized additive mixed models or functional data analysis methods), and the use of Bayesian methods. This shift has been driven in part by the increased focus on large speech corpora in phonetics, which has arisen from machine learning methods such as forced alignment. We conclude by identifying opportunities for future research.

中文翻译：

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 语音统计学


语音学是一门科学领域，涉及研究语音如何产生、听到和感知。它包含大量数据，例如声学语音记录、神经影像学数据或发音数据。在本文中，我们介绍了语音学的不同领域（声学、社会语音学、语音感知、发音语音学、语音倒置、声音变化和语音技术），概述了分析数据的统计方法，并介绍了通常用于语音记录的信号处理方法。语音数据统计建模的一个主要转变是从固定效应到随机效应回归模型的转变，曲线数据的建模（例如，通过广义加性混合模型或函数数据分析方法）以及贝叶斯方法的使用。这种转变部分是由于语音学中对大型语音语料库的日益关注，这是由强制对齐等机器学习方法引起的。最后，我们确定了未来研究的机会。