TY - JOUR

T1 - The Semantics - Syntax Interface

T2 - Learning Grammatical Categories and Hierarchical Syntactic Structure through Semantics

AU - Poletiek, Fenna H.

AU - Monaghan, Padraic

AU - van de Velde, Maartje

AU - Bocanegra, Bruno

N1 - ©American Psychological Association, 2021. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at: 10.1037/xlm000104410.1037/xlm0001044

PY - 2021/10/25

Y1 - 2021/10/25

N2 - Language is infinitely productive because syntax defines dependencies between grammatical categories of words and constituents, so there is interchangeability of these words and constituents within syntactic structures. Previous laboratory-based studies of language learning have shown that complex language structures like hierarchical center embeddings (HCE) are very hard to learn, but these studies tend to simplify the language learning task, omitting semantics and focusing either on learning dependencies between individual words or on acquiring the category membership of those words. We tested whether categories of words and dependencies between these categories and between constituents, could be learned simultaneously in an artificial language with HCE’s, when accompanied by scenes illustrating the sentence’s intended meaning. Across four experiments, we showed that participants were able to learn the HCE language varying words across categories and category-dependencies, and constituents across constituents-dependencies. They also were able to generalize the learned structure to novel sentences and novel scenes that they had not previously experienced. This simultaneous learning resulting in a productive complex language system, may be a consequence of grounding complex syntax acquisition in semantics.

AB - Language is infinitely productive because syntax defines dependencies between grammatical categories of words and constituents, so there is interchangeability of these words and constituents within syntactic structures. Previous laboratory-based studies of language learning have shown that complex language structures like hierarchical center embeddings (HCE) are very hard to learn, but these studies tend to simplify the language learning task, omitting semantics and focusing either on learning dependencies between individual words or on acquiring the category membership of those words. We tested whether categories of words and dependencies between these categories and between constituents, could be learned simultaneously in an artificial language with HCE’s, when accompanied by scenes illustrating the sentence’s intended meaning. Across four experiments, we showed that participants were able to learn the HCE language varying words across categories and category-dependencies, and constituents across constituents-dependencies. They also were able to generalize the learned structure to novel sentences and novel scenes that they had not previously experienced. This simultaneous learning resulting in a productive complex language system, may be a consequence of grounding complex syntax acquisition in semantics.

KW - semantics

KW - language learning

KW - artificial grammar learning

KW - center embedded hierarchical grammar

KW - syntactic category learning

U2 - 10.1037/xlm0001044

DO - 10.1037/xlm0001044

M3 - Journal article

VL - 47

SP - 1141

EP - 1155

JO - Journal of Experimental Psychology: Learning, Memory, and Cognition

JF - Journal of Experimental Psychology: Learning, Memory, and Cognition

SN - 0278-7393

IS - 7

ER -