{"default": {"description": "Livonian is one of the most endangered languages in Europe with just a tiny handful of speakers and virtually no publicly available corpora. \nIn this paper we tackle the task of developing neural machine translation (NMT) between Livonian and English, with a two-fold aim: on one hand, \npreserving the language and on the other \u2013 enabling access to Livonian folklore, lifestories and other textual intangible heritage as well as \nmaking it easier to create further parallel corpora. We rely on Livonian's linguistic similarity to Estonian and Latvian and collect parallel \nand monolingual data for the four languages for translation experiments. We combine different low-resource NMT techniques like zero-shot translation, \ncross-lingual transfer and synthetic data creation to reach the highest possible translation quality as well as to find which base languages are \nempirically more helpful for transfer to Livonian. The resulting NMT systems and the collected monolingual and parallel data, including a manually \ntranslated and verified translation benchmark, are publicly released.\n\nFields:\n- source: source of the data\n- en: sentence in English\n- liv: sentence in Livonian\n", "citation": "@inproceedings{rikters-etal-2022,\n    title = \"Machine Translation for Livonian: Catering for 20 Speakers\",\n    author = \"Rikters, Mat\u012bss  and\n      Tomingas, Marili and\n      Tuisk, Tuuli and\n      Valts, Ern\u0161treits  and\n      Fishel, Mark\",\n    booktitle = \"Proceedings of ACL 2022\",\n    year = \"2022\",\n    address = \"Dublin, Ireland\",\n    publisher = \"Association for Computational Linguistics\"\n}\n", "homepage": "https://huggingface.co/datasets/tartuNLP/liv4ever", "license": "CC BY-NC-SA 4.0", "features": {"source": {"dtype": "string", "id": null, "_type": "Value"}, "en": {"dtype": "string", "id": null, "_type": "Value"}, "liv": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "liv4ever", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 170909, "num_examples": 764, "dataset_name": "liv4ever"}, "validation": {"name": "validation", "num_bytes": 99063, "num_examples": 503, "dataset_name": "liv4ever"}, "test": {"name": "test", "num_bytes": 138178, "num_examples": 749, "dataset_name": "liv4ever"}}, "download_checksums": {"https://huggingface.co/datasets/tartuNLP/liv4ever/raw/main/train.json": {"num_bytes": 205777, "checksum": "209eac793a1b125fc3a2785be762e892f918d946a3d3be7c0ec711a6d6fcfef7"}, "https://huggingface.co/datasets/tartuNLP/liv4ever/raw/main/dev.json": {"num_bytes": 130362, "checksum": "cb7cedf67de81f537396a4b0d744d88fa445654a2c4b96c366c4ed5330df626f"}, "https://huggingface.co/datasets/tartuNLP/liv4ever/raw/main/test.json": {"num_bytes": 184301, "checksum": "ca8859e126123d7aa5e56561a27064deefe6c05fbd8a34670d13862e2cdb9ce2"}}, "download_size": 520440, "post_processing_size": null, "dataset_size": 408150, "size_in_bytes": 928590}}