How Speech and Representational Gestures Align in Child-Directed Language: a Corpus-based Study

Autor: Wang, Yumeng, Donnellan, Ed, Vigliocco, Gabriella
Rok vydání: 2023
Předmět:
Zdroj: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 45, iss 45
Popis: Representational gestures are co-speech gestures that carry semantic content related to the content of speech. Previous studies focusing on adult-adult conversation have investigated the temporal alignment of gestures and speech finding that the overwhelming majority of representational gestures are produced right before the lexical content they refer to (their lexical affiliate, LA). However, nothing is yet known about whether caregivers would also time their gestures in the same way in naturalistic interactions. We annotated representational gestures from a large corpus (ECOLANG) of semi-naturalistic conversations between caregivers and their 3-4 year old children (n = 899 gestures from n=36 caregivers). We found that, just as in adult-directed language (ADL), representational gestures in child-directed language (CDL) were more tightly linked to the onset of LAs than the onset of the utterance in which LAs were produced (hence planned when full events are encoded); with the overall majority of the representational gestures starting before their LAs. We further found that age of acquisition (AoA) rating of the LA had a significant effect on the speech-gesture latency. We found that for words acquired earlier, the gesture’s stroke (the meaningful part of a gesture) tended to be produced before the LA’s onset; for the later acquired word, the stroke tended to be produced at the same time or after the onset of the LA in speech. Our findings suggest that: (1) Regardless of their addressee, speakers always time the production of representational gestures to specific conceptual/linguistic units, rather than the full event/utterance. (2) In contrast to ADL, caregivers’ gestures may support addresses’ linguistic processing not only by supporting word prediction (of likely better-known words), but also by supporting the learning of conceptual features (of likely less well-known words).
Databáze: OpenAIRE