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SEACrowd/oil

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Hugging Face2024-06-24 更新2024-06-29 收录
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资源简介:
OIL(Online Indonesian Learning)数据集或语料库目前包含来自三位印度尼西亚教师在YouTube上发布的内容。这些内容主要用于印度尼西亚语和英语的学习。

OIL(Online Indonesian Learning)数据集或语料库目前包含来自三位印度尼西亚教师在YouTube上发布的内容。这些内容主要用于印度尼西亚语和英语的学习。
提供机构:
SEACrowd
原始信息汇总

Online Indonesian Learning (OIL) 数据集

概述

  • 名称: Online Indonesian Learning (OIL)
  • 语言: 英语 (eng), 印尼语 (ind)
  • 内容: 包含三位印尼教师在YouTube上发布的课程内容。

版本

  • 源版本: 1.0.0
  • SEACrowd版本: 2024.06.20

许可证

  • 类型: Creative Commons Attribution Non Commercial No Derivatives 4.0 (cc-by-nc-nd-4.0)

引用

  • 引用格式:

    @inproceedings{maxwelll-smith-foley-2023-automated, title = "Automated speech recognition of {I}ndonesian-{E}nglish language lessons on {Y}ou{T}ube using transfer learning", author = "Maxwell-Smith, Zara and Foley, Ben", editor = "Serikov, Oleg and Voloshina, Ekaterina and Postnikova, Anna and Klyachko, Elena and Vylomova, Ekaterina and Shavrina, Tatiana and Le Ferrand, Eric and Malykh, Valentin and Tyers, Francis and Arkhangelskiy, Timofey and Mikhailov, Vladislav", booktitle = "Proceedings of the Second Workshop on NLP Applications to Field Linguistics", month = may, year = "2023", address = "Dubrovnik, Croatia", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.fieldmatters-1.1", doi = "10.18653/v1/2023.fieldmatters-1.1", pages = "1--16", abstract = "Experiments to fine-tune large multilingual models with limited data from a specific domain or setting has potential to improve automatic speech recognition (ASR) outcomes. This paper reports on the use of the Elpis ASR pipeline to fine-tune two pre-trained base models, Wav2Vec2-XLSR-53 and Wav2Vec2-Large-XLSR-Indonesian, with various mixes of data from 3 YouTube channels teaching Indonesian with English as the language of instruction. We discuss our results inferring new lesson audio (22-46% word error rate) in the context of speeding data collection in diverse and specialised settings. This study is an example of how ASR can be used to accelerate natural language research, expanding ethically sourced data in low-resource settings.", }

    @article{lovenia2024seacrowd, title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya}, year={2024}, eprint={2406.10118}, journal={arXiv preprint arXiv: 2406.10118} }

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