The “Starting-Small” Effect in Phonology: Evidence From Biased Learning of Opaque and Transparent Vowel Harmony

The starting-small effect is a cognitive advantage in language acquisition when learners begin by generalizing on regularities from structurally simple and shorter tokens in a skewed input distribution. Our study explored this effect as a potential explanation for the biased learning of opaque and t...

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Bibliographic Details
Published inLanguage and speech Vol. 68; no. 1; pp. 3 - 35
Main Author Chen, Tsung-Ying
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.03.2025
Sage Publications Ltd
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Summary:The starting-small effect is a cognitive advantage in language acquisition when learners begin by generalizing on regularities from structurally simple and shorter tokens in a skewed input distribution. Our study explored this effect as a potential explanation for the biased learning of opaque and transparent vowel harmony. In opaque vowel harmony, feature agreement occurs strictly between adjacent vowels, and an intervening “neutral vowel” blocks long-distance vowel harmony. Thus, opaque vowel harmony could be acquired even if learners start with structurally simpler and more frequent disyllabic tokens. Alternatively, transparent vowel harmony can only be observed in longer tokens demonstrating long-distance agreement by skipping a neutral vowel. Opaque vowel harmony is predicted to be learned more efficiently due to its compatibility with local dependency acquired via starting-small learning. In two artificial grammar learning experiments, learners were exposed to both vowel harmony patterns embedded in an equal number of disyllabic and trisyllabic tokens or a skewed distribution with twice as many disyllabic tokens. In Exp I, learners’ test performance suggests the consistently biased learning of local and opaque vowel harmony with starting-small learning. Furthermore, in Exp II, the acquired vowel harmony patterns varied significantly by working memory capacity with a balanced but not skewed input distribution, presumably because of the ease of cognitive demand with starting-small learning.
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ISSN:0023-8309
1756-6053
1756-6053
DOI:10.1177/00238309241230625