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阿拉伯语龈塞音的音高和重音:语音补偿的证据。

Voice and Emphasis in Arabic Coronal Stops: Evidence for Phonological Compensation.

机构信息

Qatar University, Qatar.

出版信息

Lang Speech. 2022 Mar;65(1):73-104. doi: 10.1177/0023830920986821. Epub 2021 Jan 18.

Abstract

The current study investigates multiple acoustic cues-voice onset time (VOT), spectral center of gravity (SCG) of burst, pitch (F0), and frequencies of the first (F1) and second (F2) formants at vowel onset-associated with phonological contrasts of voicing and emphasis in production of Arabic coronal stops. The analysis of the acoustic data collected from eight native speakers of the Qatari dialect showed that the three stops form three distinct modes on the VOT scale: [d] is (pre)voiced, voiceless [t] is aspirated, and emphatic [ṭ] is voiceless unaspirated. The contrast is also maintained in spectral cues. Each cue influences production of coronal stops while their relevance to phonological contrasts varies. VOT was most relevant for voicing, but F2 was mostly associated with emphasis. The perception experiment revealed that listeners were able to categorize ambiguous tokens correctly and compensate for phonological contrasts. The listeners' results were used to evaluate three categorization models to predict the intended category of a coronal stop: a model with unweighted and unadjusted cues, a model with weighted cues compensating for phonetic context, and a model with weighted cues compensating for the voicing and emphasis contrasts. The findings suggest that the model with phonological compensation performed most similar to human listeners both in terms of accuracy rate and error pattern.

摘要

本研究调查了多种声学线索——嗓音起始时间(VOT)、爆发的频谱重心(SCG)、音高(F0)以及元音起始时的第一(F1)和第二(F2)共振峰的频率——与阿拉伯语齿龈塞音产生中的发音和重音的音系对比相关。对来自 8 位卡塔尔方言母语者的声学数据的分析表明,这三个塞音在 VOT 尺度上形成了三个不同的模式:[d]是(预)浊音,清音[t]是送气音,强调音[ṭ]是清音不送气音。这种对比在频谱线索中也得到了保持。每个线索都会影响齿龈塞音的产生,但其与音系对比的相关性有所不同。VOT 对浊音最相关,但 F2 与重音最相关。感知实验表明,听者能够正确地对模棱两可的音位进行分类,并对音系对比进行补偿。听者的结果被用来评估三种分类模型,以预测一个齿龈塞音的预期类别:一个带有未加权和未调整线索的模型,一个带有补偿语音环境的加权线索的模型,以及一个带有补偿浊音和重音对比的加权线索的模型。研究结果表明,在准确性和错误模式方面,带有音系补偿的模型与人类听者最为相似。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c915/9185181/cd6e1f0157c7/10.1177_0023830920986821-fig1.jpg

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