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# Universal Dependencies and Semantics for English and Hebrew Child-directed Speech

**Authors:** [Ida Szubert](https://md.mova.elamur.ai/free/en/docs/papers/authors/ida-szubert/), [Omri Abend](https://md.mova.elamur.ai/free/en/docs/papers/authors/omri-abend/), [Nathan Schneider](https://md.mova.elamur.ai/free/en/docs/papers/authors/nathan-schneider/), [Samuel Gibbon](https://md.mova.elamur.ai/free/en/docs/papers/authors/samuel-gibbon/), [Sharon Goldwater](https://md.mova.elamur.ai/free/en/docs/papers/authors/sharon-goldwater/), [Mark Steedman](https://md.mova.elamur.ai/free/en/docs/papers/authors/mark-steedman/) · **Year:** 2022 · **Venue:** Proceedings of the Society for Computation in Linguistics 2022 **Link:** [aclanthology.org/2022.scil-1.24](https://aclanthology.org/2022.scil-1.24/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[Proceedings of the Society for Computation in Linguistics 2022](https://aclanthology.org/volumes/2022.scil-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2022.scil-1.24/)
- [PDF](https://aclanthology.org/2022.scil-1.24.pdf)

**Authors (6)**

1. Ida Szubert
2. Omri Abend
3. Nathan Schneider
4. Samuel Gibbon
5. Sharon Goldwater
6. Mark Steedman

Citations and author metrics from OpenAlex (); authors with the same name are not always told apart.

## What it is about

The authors annotate child-directed speech in English (the Adam corpus of CHILDES, 18,113 utterances) and Hebrew (the Hagar corpus, 24,172 utterances) with UD, and then convert the UD trees into logical forms, a meaning representation for acquisition models. Annotators agree at LAS 89.9 on English and 86.7 on Hebrew. Parser pre-annotations were altered on about 40% of English edges and 30% of Hebrew edges, so the automatic output needed much correction. The UD-to-logical-form conversion covers about 80% of the utterances. The paper's aim is a meaning layer that works across languages, so one conversion can serve several child corpora.

## Ideas

- I1. `prag` and `world`: a conversion of UD trees to event-argument forms, measured by the share of clauses it converts on EWT and on the Adam utterances, against the 80% coverage reported here.
- I2. `annot`: count how many edges an `en` or LLM pre-annotation changes during review on child-directed utterances, as the paper's edit rate; a review cost measure for the school corpus.
- I3. `en parse-eval` on the Adam child-directed utterances, as a test set of short, repetitive input (test only, licence per the data).

## For Mova

The conversion from trees to logical forms is what `prag` does for Mova, so the coverage figure is a direct comparison. Child-directed speech is also the register of Mova's school material. Relevant chapters are `languages/en/21-clause-structure` and `38-dialogue-and-discourse-markers`. Measure first the coverage of the event conversion on EWT, then on the Adam utterances.

Topics: [Universal Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/topics/universal-dependencies/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work.

```
@inproceedings{szubert2022universal,
  title = {{Universal Dependencies and Semantics for English and Hebrew Child-directed Speech}},
  author = {Szubert, Ida and Abend, Omri and Schneider, Nathan and Gibbon, Samuel and Goldwater, Sharon and Steedman, Mark},
  booktitle = {Proceedings of the Society for Computation in Linguistics 2022},
  year = {2022},
  url = {https://aclanthology.org/2022.scil-1.24/}
}
```

- [← previous Nucleus Composition in Transition-based Dependency Parsing](https://md.mova.elamur.ai/free/en/docs/papers/ud-2022-nivre-nucleus-composition-transition-based-dependency/)
- [next → The Aligned Multimodal Movie Treebank: An audio, video, dependency-parse treebank](https://md.mova.elamur.ai/free/en/docs/papers/ud-2022-yaari-aligned-multimodal-movie-treebank-audio/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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