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arXiv 2407.05092cs.CL
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探索随时间演变的语音变化:计算与人类感知综述

Exploring Sound Change Over Time: A Review of Computational and Human Perception

Shanghai Jiao Tong University(上海交通大学);University of Heidelberg(海德堡大学);University of Aberdeen(阿伯丁大学)

Siqi He, Wei Zhao

AI总结:

本文综述计算与人类感知两类语音变化研究,比较其方法、任务、数据与互补性,并呼吁开展跨数据集比较及关注语言变化的多层复杂性。

摘要:

计算感知与人类感知通常被视为研究随时间演变的语音变化的两种不同方法;很少有研究涉及二者的交叉领域。为填补这一研究空白,本文提供了一项开创性综述,从方法和任务的角度对计算方法与人类感知进行对比。总体而言,计算方法依赖计算机驱动的模型,在词源数据集上感知历史语音变化;而人类方法则使用听者驱动的模型,在录音语料库上感知正在发生的语音变化。尽管存在差异,两种方法在语音和声学层面互为补充,展现出实现更全面的语音变化感知的潜力。此外,本文呼吁对两种方法所使用的数据集开展比较研究,以考察历史语音变化对正在发生的变化的影响。最后,本文讨论了语音变化在计算语言学中的应用,并指出仅感知语音变化并不充分,因为许多语言变化过程十分复杂,句法、语义和语音层面的变化相互交织。

英文摘要:

Computational and human perception are often considered separate approaches for studying sound changes over time; few works have touched on the intersection of both. To fill this research gap, we provide a pioneering review contrasting computational with human perception from the perspectives of methods and tasks. Overall, computational approaches rely on computer-driven models to perceive historical sound changes on etymological datasets, while human approaches use listener-driven models to perceive ongoing sound changes on recording corpora. Despite their differences, both approaches complement each other on phonetic and acoustic levels, showing the potential to achieve a more comprehensive perception of sound change. Moreover, we call for a comparative study on the datasets used by both approaches to investigate the influence of historical sound changes on ongoing changes. Lastly, we discuss the applications of sound change in computational linguistics, and point out that perceiving sound change alone is insufficient, as many processes of language change are complex, with entangled changes at syntactic, semantic, and phonetic levels.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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