Sound symbolism emerged as a prevalent component in the origin and development of language. However, as previous studies have either been lacking in scope or in phonetic granularity, the present study investigates the phonetic and semantic features involved from a bottom-up perspective. By analyzing the phonemes of 344 near-universal concepts in 245 language families, we establish 125 sound-meaning associations. The results also show that between 19 and 40 of the items of the Swadesh-100 list are sound symbolic, which calls into question the list’s ability to determine genetic relationships. In addition, by combining co-occurring semantic and phonetic features between the sound symbolic concepts, 20 macro-concepts can be identified, e. g. basic descriptors, deictic distinctions and kinship attributes. Furthermore, all identified macro-concepts can be grounded in four types of sound symbolism: (a) unimodal imitation (onomatopoeia); (b) cross-modal imitation (vocal gestures); (c) diagrammatic mappings based on relation (relative); or (d) situational mappings (circumstantial). These findings show that sound symbolism is rooted in the human perception of the body and its interaction with the surrounding world, and could therefore have originated as a bootstrapping mechanism, which can help us understand the bio-cultural origins of human language, the mental lexicon and language diversity.

This article investigates the evolutionary and spatial dynamics of typological characters in 117 Indo-European languages. We partition types of change (i.e., gain or loss) for each variant according to whether they bring about a simplification in morphosyntactic patterns that must be learned, whether they are neutral (i.e., neither simplifying nor introducing complexity) or whether they introduce a more complex pattern. We find that changes which introduce complexity show significantly less areal signal (according to a metric we devise) than changes which simplify and neutral changes, but we find no significant differences between the latter two groups. This result is compatible with a scenario where certain types of parallel change are more likely to be mediated by advergence and contact between proximate speech communities, while other developments are due purely to drift and are largely independent of intercultural contact.

This study uses phylogenetic methods adopted from computational biology in order to reconstruct features of Proto-Indo-European morphosyntax. We estimate the probability of the presence of typological features in Proto-Indo-European on the assumption that these features change according to a stochastic process governed by evolutionary transition rates between them. We compare these probabilities to previous reconstructions of Proto-Indo-European morphosyntax, which use either the comparative-historical method or implicational typology. We find that our reconstruction yields strong support for a canonical model (synthetic, nominative-accusative, headfinal) of the protolanguage and low support for any alternative model. Observing the evolutionary dynamics of features in our data set, we conclude that morphological features have slower rates of change, whereas syntactic traits change faster. Additionally, more frequent, unmarked traits in grammatical hierarchies have slower change rates when compared to less frequent, marked ones, which indicates that universal patterns of economy and frequency impact language change within the family.

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Feature stability, time and tempo of change, and the role of genealogy versus areality in creating linguistic diversity are important issues in current computational research on linguistic typology. This paper presents a database initiative, DiACL Typology, which aims to provide a resource for addressing these questions with specific of the extended Indo-European language area of Eurasia, the region with the best documented linguistic history. The database is pre-prepared for statistical and phylogenetic analyses and contains both linguistic typological data from languages spanning over four millennia, and linguistic metadata concerning geographic location, time period, and reliability of sources. The typological data has been organized according to a hierarchical model of increasing granularity in order to create datasets that are complete and representative.