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--- |
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language: |
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- fr |
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license: mit |
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task_categories: |
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- translation |
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tags: |
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- pictograms |
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- AAC |
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pretty_name: Propicto-polylexical |
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--- |
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# Propicto-polylexical |
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## 📝 Dataset Description |
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Propicto-polylexical is a dataset of aligned text and pictograms (the pictograms correspond to the identifiers associated with ARASAAC pictograms) in French. |
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This dataset was manually created to specifically provide a resource containing texts with polylexical expressions translated into pictograms. |
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The dataset contains is a single file of 1,462 utterances. |
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## ⚒️ Dataset Structure |
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The dataset is structured as follows: |
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```csv |
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id : the unique identifier of the utterance |
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text : the sentence in French |
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pictos : the sequence of pictogram IDs from ARASAAC |
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tokens : the sequence of tokens, each of which is a keyword associated with an ARASAAC pictogram ID |
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``` |
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## 💡 Dataset example |
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For the given sample : |
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```csv |
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id : 43 |
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text : le collier du chien est trop serré il faut l'ajuster |
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pictos : [8476, 6987, 36480, 25708, 5380, 15523, 8476, 8516] |
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tokens : le collier_du_chien être trop serrer devoir le adapter |
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``` |
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- `pictos` is the sequence of pictogram IDs, each of them can be retrieved from here : 15523 = https://static.arasaac.org/pictograms/15523/15523_2500.png<br /> |
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- `tokens` are retrieved from a specific lexicon and can be used to train translation models. |
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## 💻 Uses |
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Propicto-polylexical is intended to be used to train Text-to-Pictograms translation models. |
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This dataset can also be used to fine-tune large language models to perform translation into pictograms. |
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## ⚙️ Dataset Creation |
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The dataset is created by applying a specific formalism that converts french transcriptions into a corresponding sequence of pictograms.<br /> |
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The formalism includes a set of grammatical rules to handle specific phenomenon (negation, name entities, pronominal form, plural, ...) to the French language, as well as a dictionary which associates each ARASAAC ID pictogram with a set of keywords (tokens).<br /> |
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This formalism was presented at [LREC](https://aclanthology.org/2024.lrec-main.76/). |
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## ⁉️ Limitations |
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The translation can be partially incorrect, due to incorrect or missing words translated into pictograms. |
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## 💡 Information |
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- **Curated by:** Cécile MACAIRE |
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- **Funded by :** [PROPICTO ANR-20-CE93-0005](https://anr.fr/Projet-ANR-20-CE93-0005) |
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- **Language(s) (NLP):** French |
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- **License:** CC-BY-NC-SA-4.0 |
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## 📌 Citation |
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```bibtex |
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@inproceedings{macaire-etal-2024-multimodal, |
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title = "A Multimodal {F}rench Corpus of Aligned Speech, Text, and Pictogram Sequences for Speech-to-Pictogram Machine Translation", |
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author = "Macaire, C{\'e}cile and |
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Dion, Chlo{\'e} and |
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Arrigo, Jordan and |
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Lemaire, Claire and |
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Esperan{\c{c}}a-Rodier, Emmanuelle and |
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Lecouteux, Benjamin and |
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Schwab, Didier", |
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booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)", |
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year = "2024", |
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publisher = "ELRA and ICCL", |
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url = "https://aclanthology.org/2024.lrec-main.76", |
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pages = "839--849", |
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} |
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``` |
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## 👩🏫 Dataset Card Authors |
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**Cécile MACAIRE, Chloé DION, Emmanuelle ESPÉRANÇA-RODIER, Benjamin LECOUTEUX, Didier SCHWAB** |
