ERC Consolidator Grant
Yesterday, the ERC offially announced the winners of the Consolidator Grant applications from 2021. I am very proud that my project ProduSemy -- Productive Signs. A Computer-Assisted Analysis of Evolutionary, Typological, and Cognitive Dimensions of Word Families -- was among the projects that were selected for funding (see the announcement of the project in our institute here). The abstract of the project is given below:
All human languages have simple and complex words. Simple words refer to meanings regardless of their form, while complex words are formed from other words, and their formation can be semantically motivated. Since words can share lexical material, we can group them into families. Word families can vary greatly in size, ranging from small ones – comprising only a few members –, to large ones – spanning several hundred words –, but it is still unclear why some words are more productive than others in forming new words. Lexical composi- tionality has received some attention in historical linguistics, linguistic typology, and cognitive linguistics, but so far studies have mostly concentrated on the morphological complexity of individual words and languages, while the fact that words form families which interact during language change and language use has been typically ignored. As a result, many questions regarding word family formation remain unresolved, and we do not know (1) how word families evolve along language phylogenies, (2) which semantic processes underlying word family formation are universal, and (3) to what extent human cognition influences the productivity of lexical roots to form families. The project will tackle these three target questions by unifying evolutionary, typological, and cognitive insights into lexical compositionality. Building on a computer-assisted framework that reconciles classical and computational approaches in historical linguistics and linguistic typology, the project will design new models to standardize cross-linguistic data on word families, apply them to integrate data from historical linguistics, linguistic typology, and cognitive linguistics, and develop new methods for the computer-assisted inference of word families, their underlying motivation patterns, and their evolutionary histories in large datasets. In this way, the project will deepen the integration of cross-linguistic studies in cognitive and psychological sciences.
With a project start planned for October, and the CALC³ project starting already in April, the CALC lab, which lost some of its members recently, due to the end of the ERC Starting Grant that funded the first five years of the project, will welcome new members in the future and pursue the research on computer-assisted language comparison, this time with a specific focus on the compositionality of the human lexicon.