Domain Generalization in Artificial Language Learning

Abstract

Many languages have restrictions on word-final segments, such as a requirement that any word-final obstruent be voiceless. There is a phonetic basis for such restrictions at the ends of utterances, but not the ends of words. Historical linguists have long noted this mismatch, and have attributed it to an analogical generalization of such restrictions from utterance-final to word-final position. To test whether language learners actually generalize in this way, two artificial language learning experiments were conducted. Participants heard nonsense sentences in which there was a restriction on utterance-final obstruents, but in which no information was available about word-final, utterance-medial obstruents. They were then tested on utterances that included obstruents in both positions. They learned the pattern and generalized it to word-final utterance-medial position, confirming that learners are biased toward word-based distributional patterns

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