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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- it |
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- lld |
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--- |
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# Ladin-Val Badia to Italian Translation Model |
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## Description |
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This model is designed for translating text between Ladin (Val Badia) and Italian. |
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The model was developed and trained as part of the research presented in the paper titled |
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"Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladin" submitted to [LoResMT @ ACL 2024](https://sites.google.com/view/loresmt/). |
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## Paper |
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The details of the model, including its architecture, training process, and evaluation, are discussed in the paper: |
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- [Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladin](https://arxiv.org/abs/2407.08819) |
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## License |
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This model is licensed under the [CC BY-NC-SA 4.0 License](https://creativecommons.org/licenses/by-nc-sa/4.0/). |
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## Usage |
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To use this model for translation, you need to use the prefixes `>>ita<<` for translating to Italian and `>>lld_Latn<<` for translating to Ladin (Val Badia). |
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--- |
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license: cc-by-nc-sa-4.0 |
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language: |
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- it |
|
- lld |
|
--- |
|
|
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# Ladin-Val Badia to Italian Translation Model |
|
|
|
## Description |
|
This model is designed for translating text between Ladin (Val Badia) and Italian. |
|
The model was developed and trained as part of the research presented in the paper titled |
|
"Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladin" submitted to [LoResMT @ ACL 2024](https://sites.google.com/view/loresmt/). |
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## Paper |
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The details of the model, including its architecture, training process, and evaluation, are discussed in the paper: |
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- [Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladin](https://arxiv.org/abs/2407.08819) |
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## License |
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This model is licensed under the [CC BY-NC-SA 4.0 License](https://creativecommons.org/licenses/by-nc-sa/4.0/). |
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## Usage |
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To use this model for translation, you need to use the prefixes `>>ita<<` for translating to Italian and `>>lld_Latn<<` for translating to Ladin (Val Badia). |
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## Citation |
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If you use this model, please cite the following paper: |
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```bibtex |
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@inproceedings{frontull-moser-2024-rule, |
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title = "Rule-Based, Neural and {LLM} Back-Translation: Comparative Insights from a Variant of {L}adin", |
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author = "Frontull, Samuel and |
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Moser, Georg", |
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editor = "Ojha, Atul Kr. and |
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Liu, Chao-hong and |
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Vylomova, Ekaterina and |
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Pirinen, Flammie and |
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Abbott, Jade and |
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Washington, Jonathan and |
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Oco, Nathaniel and |
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Malykh, Valentin and |
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Logacheva, Varvara and |
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Zhao, Xiaobing", |
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booktitle = "Proceedings of the The Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024)", |
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month = aug, |
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year = "2024", |
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address = "Bangkok, Thailand", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2024.loresmt-1.13", |
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pages = "128--138", |
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abstract = "This paper explores the impact of different back-translation approaches on machine translation for Ladin, specifically the Val Badia variant. Given the limited amount of parallel data available for this language (only 18k Ladin-Italian sentence pairs), we investigate the performance of a multilingual neural machine translation model fine-tuned for Ladin-Italian. In addition to the available authentic data, we synthesise further translations by using three different models: a fine-tuned neural model, a rule-based system developed specifically for this language pair, and a large language model. Our experiments show that all approaches achieve comparable translation quality in this low-resource scenario, yet round-trip translations highlight differences in model performance.", |
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} |
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``` |
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