The present paper addresses the study of non-arbitrariness in language within a deep learning framework. We present a set of experiments aimed at assessing the pervasiveness of different forms of non-arbitrary phonological patterns across a set of typologically distant languages. Different sequence-processing neural networks are trained in a set of languages to associate the phonetic vectorization of a set of words to their sensory (Experiment 1), semantic (Experiment 2), and word-class representations (Experiment 3). The models are then tested, without further training, in a set of novel instances in a language belonging to a different language family, and their performance is compared with a randomized baseline. We show that the three cross-domain mappings can be successfully transferred across languages and language families, suggesting that the phonological structure of the lexicon is pervaded with language-invariant cues about the words' meaning and their syntactic classes.

A Cross‐Modal and Cross‐lingual Study of Iconicity in Language: Insights From Deep Learning

Carlo Strapparava
2022

Abstract

The present paper addresses the study of non-arbitrariness in language within a deep learning framework. We present a set of experiments aimed at assessing the pervasiveness of different forms of non-arbitrary phonological patterns across a set of typologically distant languages. Different sequence-processing neural networks are trained in a set of languages to associate the phonetic vectorization of a set of words to their sensory (Experiment 1), semantic (Experiment 2), and word-class representations (Experiment 3). The models are then tested, without further training, in a set of novel instances in a language belonging to a different language family, and their performance is compared with a randomized baseline. We show that the three cross-domain mappings can be successfully transferred across languages and language families, suggesting that the phonological structure of the lexicon is pervaded with language-invariant cues about the words' meaning and their syntactic classes.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/332868
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