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Data-driven Parsing Evaluation for Child-Parent Interactions

What it is about

The authors build a UD-style treebank of spoken child-parent interactions from CHILDES: 44,744 utterances and 233,907 words from 10 children aged 18 to 66 months. Their guidelines extend UD for speech repairs, restarts, repetition and other spoken structures. Three parsers (Diaparser, MaChamp, UUParser) are trained on written out-of-domain data: EWT, Tweebank and ESL. The best out-of-domain parsers reach LAS of about 83.9 on parent data (ESL, twitter language model) and about 79.4 on child data. LAS for child data rises with age, mostly between 18 and 48 months, and the effect of utterance length is small and negative. In-domain training helps a little.

Ideas

For Mova

This is a second CHILDES treebank with its own guidelines, useful as an out-of-domain test of en for child speech. The age curve is a result about the input that Mova's parser may also show. Relevant chapters are languages/en/21-clause-structure and 38-dialogue-and-discourse-markers. Measure first the LAS of en by age band on this treebank, with the parent and child halves reported separately.

Topics: Treebanks

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.1162/tacl_a_00624 · arXiv 2209.13778

@article{liu2023data,
  title = {{Data-driven Parsing Evaluation for Child-Parent Interactions}},
  author = {Liu, Zoey and Prud'hommeaux, Emily},
  journal = {Transactions of the Association for Computational Linguistics},
  year = {2023},
  doi = {10.1162/tacl\_a\_00624},
  eprint = {2209.13778},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.1162/tacl_a_00624}
}

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