{
 "id": "SEACrowd/parallel_id_nyo",
 "owner": "SEACrowd",
 "name": "parallel_id_nyo",
 "downloads": 35,
 "likes": 0,
 "last_modified": "2024-06-24T13:33:08.000Z",
 "stated_licence": null,
 "stated_from": "none",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [
  "LICENSE"
 ],
 "sources": [],
 "gated": false,
 "tasks": [
  "machine-translation"
 ],
 "citation": "@article{Abidin_2021,\ndoi = {10.1088/1742-6596/1751/1/012036},\nurl = {https://dx.doi.org/10.1088/1742-6596/1751/1/012036},\nyear = {2021},\nmonth = {jan},\npublisher = {IOP Publishing},\nvolume = {1751},\nnumber = {1},\npages = {012036},\nauthor = {Z Abidin and  Permata and I Ahmad and  Rusliyawati},\ntitle = {Effect of mono corpus quantity on statistical machine translation\nIndonesian - Lampung dialect of nyo},\njournal = {Journal of Physics: Conference Series},\nabstract = {Lampung Province is located on the island of Sumatera. For the\nimmigrants in Lampung, they have difficulty in\ncommunicating with the indigenous people of Lampung. As an alternative, both\nimmigrants and the indigenous people of Lampung speak Indonesian.\nThis research aims to build a language model from Indonesian language and a\n translation model from the Lampung language dialect of nyo, both models will\n be combined in a Moses decoder.\nThis research focuses on observing the effect of adding mono corpus to the\n experimental statistical machine translation of\n Indonesian - Lampung dialect of nyo.\nThis research uses 3000 pair parallel corpus in Indonesia language and\nLampung language dialect of nyo as source language\nand uses 3000 mono corpus sentences in Lampung language\ndialect of nyo as target language. The results showed that the accuracy\nvalue in bilingual evalution under-study score when using 1000 sentences,\n2000 sentences, 3000 sentences mono corpus\nshow the accuracy value of the bilingual evaluation under-st",
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 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "a9eeeff896915f19c4d2cf91b4177f1266950193",
 "stated_evidence": "https://huggingface.co/datasets/SEACrowd/parallel_id_nyo/blob/a9eeeff896915f19c4d2cf91b4177f1266950193/README.md",
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}