Abstract
This paper asks whether a distinction between production-based and perception-based grammar induction influences either (i) the growth curve of grammars and lexicons or (ii) the similarity between representations learned from independent sub-sets of a corpus. A productionbased model is trained on the usage of a single individual, thus simulating the grammatical knowledge of a single speaker. A perception-based model is trained on an aggregation of many individuals, thus simulating grammatical generalizations learned from exposure to many different speakers. To ensure robustness, the experiments are replicated across two registers of written English, with four additional registers reserved as a control. A set of three computational experiments shows that production-based grammars are significantly different from perception-based grammars across all conditions, with a steeper growth curve that can be explained by substantial inter-individual grammatical differences.
| Original language | English (US) |
|---|---|
| Title of host publication | CMCL 2021 - Workshop on Cognitive Modeling and Computational Linguistics, Proceedings |
| Editors | Emmanuele Chersoni, Nora Hollenstein, Cassandra Jacobs, Yohei Oseki, Laurent Prevot, Enrico Santus |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 149-159 |
| Number of pages | 11 |
| ISBN (Electronic) | 9781954085350 |
| DOIs | |
| State | Published - 2021 |
| Externally published | Yes |
| Event | 11th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2021 - Virtual, Online Duration: Jun 10 2021 → … |
Conference
| Conference | 11th Workshop on Cognitive Modeling and Computational Linguistics, CMCL 2021 |
|---|---|
| City | Virtual, Online |
| Period | 6/10/21 → … |
ASJC Scopus subject areas
- Language and Linguistics
- Speech and Hearing