Omkar2118/datasets huggingface dataset:
WenetSpeech

WenetSpeech is a multi-domain Mandarin corpus consisting of 10,000+ hours high-quality labeled speech, 2,400+ hours weakly labelled speech, and about 10,000 hours unlabeled speech, with 22,400+ hours in total. The authors collected the data from YouTube and Podcast, which covers a variety of speaking styles, scenarios, domains, topics, and noisy conditions. An optical character recognition (OCR) based method is introduced to generate the audio/text segmentation candidates for the YouTube data on its corresponding video captions.

Image source: [https://github.com/wenet-e2e/wenetspeech](https://github.com/wenet-e2e/wenetspeech)

Introducing paper: WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition