This paper investigates whether a curiosity-based strategy could be beneficial to word learning. Children are active conversation partners and exert considerable influence over the topics that are discussed in conversation with their parents. As the choice of topics is likely to be intrinsically motivated, a formalization of curiosity is implemented in a word learning model. The model receives annotated Flickr30k Entities images as input, and is trained in two conditions. In the curious condition, the model chooses objects to talk about from the scene according to the curiosity mechanism, whereas in the random condition, the model receives randomly chosen objects as input. The goal of this study is to show how a curious, active choice of topics by a language learner improves word learning compared to random selection. Curiosity is found to make word learning faster, increase robustness, and lead to better accuracy.
|Title of host publication||Proceedings of the 41st Annual Conference of the Cognitive Science Society|
|Place of Publication||Montreal|
|Publisher||Cognitive Science Society|
|Publication status||Published - Jul 2019|
|Event||Annual Meeting of the Cognitive Science Society 2019: Creativity + Cognition + Computation - Palais des Congrès , Montreal, Canada|
Duration: 24 Jul 2019 → 27 Jul 2019
Conference number: 41
|Conference||Annual Meeting of the Cognitive Science Society 2019|
|Abbreviated title||CogSci 2019|
|Period||24/07/19 → 27/07/19|
Keijser, D., Gelderloos, L., & Alishahi, A. (2019). Curious Topics: A Curiosity-Based Model of First Language Word Learning. In Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 1991-1997). Cognitive Science Society.