Language Acquisition through Intention Reading and Pattern Finding

Jens Nevens, Jonas Doumen, Paul Van Eecke, Katrien Beuls


Abstract
One of AI’s grand challenges consists in the development of autonomous agents with communication systems offering the robustness, flexibility and adaptivity found in human languages. While the processes through which children acquire language are by now relatively well understood, a faithful computational operationalisation of the underlying mechanisms is still lacking. Two main cognitive processes are involved in child language acquisition. First, children need to reconstruct the intended meaning of observed utterances, a process called intention reading. Then, they can gradually abstract away from concrete utterances in a process called pattern finding and acquire productive schemata that generalise over form and meaning. In this paper, we introduce a mechanistic model of the intention reading process and its integration with pattern finding capacities. Concretely, we present an agent-based simulation in which an agent learns a grammar that enables them to ask and answer questions about a scene. This involves the reconstruction of queries that correspond to observed questions based on the answer and scene alone, and the generalization of linguistic schemata based on these reconstructed question-query pairs. The result is a productive grammar which can be used to map between natural language questions and queries without ever having observed the queries.
Anthology ID:
2022.coling-1.2
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
15–25
Language:
URL:
https://aclanthology.org/2022.coling-1.2
DOI:
Bibkey:
Cite (ACL):
Jens Nevens, Jonas Doumen, Paul Van Eecke, and Katrien Beuls. 2022. Language Acquisition through Intention Reading and Pattern Finding. In Proceedings of the 29th International Conference on Computational Linguistics, pages 15–25, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Language Acquisition through Intention Reading and Pattern Finding (Nevens et al., COLING 2022)
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PDF:
https://aclanthology.org/2022.coling-1.2.pdf
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