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Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning.

ABSTRACT: Human language is composed of sequences of reusable elements. The origins of the sequential structure of language is a hotly debated topic in evolutionary linguistics. In this paper, we show that sets of sequences with language-like statistical properties can emerge from a process of cultural evolution under pressure from chunk-based memory constraints. We employ a novel experimental task that is non-linguistic and non-communicative in nature, in which participants are trained on and later asked to recall a set of sequences one-by-one. Recalled sequences from one participant become training data for the next participant. In this way, we simulate cultural evolution in the laboratory. Our results show a cumulative increase in structure, and by comparing this structure to data from existing linguistic corpora, we demonstrate a close parallel between the sets of sequences that emerge in our experiment and those seen in natural language.

SUBMITTER: Cornish H

PROVIDER: S-EPMC5261806 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning.

Cornish Hannah H Dale Rick R Kirby Simon S Christiansen Morten H MH

PloS one 20170124 1

Human language is composed of sequences of reusable elements. The origins of the sequential structure of language is a hotly debated topic in evolutionary linguistics. In this paper, we show that sets of sequences with language-like statistical properties can emerge from a process of cultural evolution under pressure from chunk-based memory constraints. We employ a novel experimental task that is non-linguistic and non-communicative in nature, in which participants are trained on and later asked ...[more]

PMID: 28118370

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