Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.12832 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909539109961728 |
|---|---|
| author | Mahon, Louis Johnson, Mark Steedman, Mark |
| author_facet | Mahon, Louis Johnson, Mark Steedman, Mark |
| contents | This work develops a probabilistic child language acquisition model to learn a range of linguistic phenonmena, most notably long-range syntactic dependencies of the sort found in object wh-questions, among other constructions. The model is trained on a corpus of real child-directed speech, where each utterance is paired with a logical form as a meaning representation. It then learns both word meanings and language-specific syntax simultaneously. After training, the model can deduce the correct parse tree and word meanings for a given utterance-meaning pair, and can infer the meaning if given only the utterance. The successful modelling of long-range dependencies is theoretically important because it exploits aspects of the model that are, in general, trans-context-free. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_12832 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modelling Child Learning and Parsing of Long-range Syntactic Dependencies Mahon, Louis Johnson, Mark Steedman, Mark Computation and Language This work develops a probabilistic child language acquisition model to learn a range of linguistic phenonmena, most notably long-range syntactic dependencies of the sort found in object wh-questions, among other constructions. The model is trained on a corpus of real child-directed speech, where each utterance is paired with a logical form as a meaning representation. It then learns both word meanings and language-specific syntax simultaneously. After training, the model can deduce the correct parse tree and word meanings for a given utterance-meaning pair, and can infer the meaning if given only the utterance. The successful modelling of long-range dependencies is theoretically important because it exploits aspects of the model that are, in general, trans-context-free. |
| title | Modelling Child Learning and Parsing of Long-range Syntactic Dependencies |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2503.12832 |