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辅音的泛化:音位对比语音

Generalization to Novel Consonants: Place Versus Voice.

机构信息

Pacific Lutheran University, Tacoma, WA, USA.

出版信息

J Psycholinguist Res. 2022 Dec;51(6):1283-1309. doi: 10.1007/s10936-022-09897-1. Epub 2022 Jun 25.

DOI:10.1007/s10936-022-09897-1
PMID:35751769
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9669126/
Abstract

In traditional, generative phonology, sound patterns are represented in terms of abstract features, typically based on the articulatory properties of the sounds. The present study makes use of an artificial language learning experiment to explore when and how learners extend a novel phonological pattern to novel segments. Adult, English-speaking learners were exposed to a spirantization pattern in which a stop became a fricative between two vowels (e.g., /bib/ + /o/ ➔ [bivo]). Participants were trained on spirantization for two of four possible stop-fricative pairs, and were tested on their generalization to the held-out segments. Two groups of participants were trained on items based on voicing (e.g., the Voiced condition was trained on /b/ ➔ [v], and /d/ ➔ [z], and tested on /p/ ➔ [f], and /t/ ➔ [s]), and two groups of participants were trained on items based on place of articulation (e.g., the Labial condition was trained on /b/ ➔ [v], and /p/ ➔ [f] and tested on /t/ ➔ [s], and /d/ ➔ [z]). Participants in both Place and Voice conditions were successful at learning and generalizing the spirantization pattern to novel segments, but rates of generalization were higher in the Voice conditions. These results support a similarity-based approach to generalization, particularly one that takes into account articulatorily-based features and natural classes. Implications for phonological theory are discussed.

摘要

在传统的生成音系学中,音系模式是用抽象特征来表示的,这些特征通常基于声音的发音特性。本研究利用人工语言学习实验来探索学习者何时以及如何将新的音系模式扩展到新的音段。成年英语学习者接触到一种连音现象,即塞音在两个元音之间变成摩擦音(例如,/bib/ + /o/ ➔ [bivo])。参与者接受了两种可能的塞音-擦音对中的两种塞音-擦音对的连音训练,并对他们对保留音段的泛化进行了测试。两组参与者分别根据发音(例如,浊音条件接受 /b/ ➔ [v] 和 /d/ ➔ [z],并测试 /p/ ➔ [f] 和 /t/ ➔ [s])和发音部位(例如,唇音条件接受 /b/ ➔ [v] 和 /p/ ➔ [f],并测试 /t/ ➔ [s] 和 /d/ ➔ [z])进行训练。位置和语音条件的参与者都成功地学习并将连音模式泛化到新的音段,但在语音条件下的泛化率更高。这些结果支持基于相似性的泛化方法,特别是考虑到基于发音特征和自然类的方法。讨论了对音系学理论的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b02/9669126/1d88a9945af3/nihms-1826015-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b02/9669126/549c3605802e/nihms-1826015-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b02/9669126/1d88a9945af3/nihms-1826015-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b02/9669126/549c3605802e/nihms-1826015-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b02/9669126/1d88a9945af3/nihms-1826015-f0002.jpg

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