Add metadata, task categories and project links
#3
by nielsr HF Staff - opened
README.md
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---
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dataset_info:
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features:
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- name: audio_id
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# Gigaspeech2 Typhoon
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**Gigaspeech2 Typhoon** is a metadata-only reference dataset for Thai speech recognition benchmarking, specifically designed as an **Accuracy Track** for evaluating ASR models. The dataset contains 1,000 test samples with audio IDs and human transcriptions derived from the [Gigaspeech2](https://arxiv.org/abs/2406.11546) corpus. Each audio_id directly links to the original Gigaspeech2 dataset, allowing users to download the corresponding audio.
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## Dataset Overview
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```bibtex
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@article{gigaspeech2_2024,
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title={GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement},
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author={
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journal={arXiv preprint arXiv:2406.11546},
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year={2024}
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}
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eprint={2601.13044},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={
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}
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```
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## Contact
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For questions or feedback about this dataset, please visit [opentyphoon.ai](http://opentyphoon.ai) or open an issue on the dataset repository.
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---
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language:
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- th
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license: cc-by-4.0
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task_categories:
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- automatic-speech-recognition
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arxiv: 2601.13044
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dataset_info:
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features:
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- name: audio_id
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# Gigaspeech2 Typhoon
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[Project page](https://opentyphoon.ai/model/typhoon-asr-realtime) | [Paper](https://huggingface.co/papers/2601.13044) | [GitHub](https://github.com/scb-10x/typhoon-asr)
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**Gigaspeech2 Typhoon** is a metadata-only reference dataset for Thai speech recognition benchmarking, specifically designed as an **Accuracy Track** for evaluating ASR models. The dataset contains 1,000 test samples with audio IDs and human transcriptions derived from the [Gigaspeech2](https://arxiv.org/abs/2406.11546) corpus. Each audio_id directly links to the original Gigaspeech2 dataset, allowing users to download the corresponding audio.
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## Dataset Overview
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```bibtex
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@article{gigaspeech2_2024,
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title={GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement},
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author={Guan-Ting Lin and others},
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journal={arXiv preprint arXiv:2406.11546},
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year={2024}
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}
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eprint={2601.13044},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2601.13044},
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}
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```
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## Contact
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For questions or feedback about this dataset, please visit [opentyphoon.ai](http://opentyphoon.ai) or open an issue on the dataset repository.
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