Multilingual Unsupervised/Weakly Supervised Speech Data | 1.1 Million Hours | Spontaneous Speech Data | Pre-training Data | Large Language Model(LLM) Data
Overview
Multilingual Unsupervised/Weakly Supervised Speech Data | 1.1 Million Hours | Spontaneous Speech Data | Pre-training Data | Large Language Model(LLM) Data is an audio dataset. Typical applications include speech recognition, LLM pre-training and conversational AI. Relevant sectors: AI & Machine Learning and Education. It is offered as a paid dataset; pricing details are provided on request.
Primary applications
1. Specifications Format: 16k Hz, 16 bit, wav, mono channel Content category: Dialogue or monologue in several common domains, such as daily vlogs, travel, podcast, technology, beauty, etc Language: English(USA, UK, Canada, Australia, India, Philippine, etc.), French, German, Japanese, Arabic(MSA, Gulf, Levantine, Egyptian accents, etc.), Southeastern Asian(Tagalog, Thai, Vitenamese, Burmese, Lao, Khmer), low-resource(Iceland, Bengali, Hausa, Javanese, Catalan, Amharic, Zulu). Recording condition: Mixed(indoor, public place, entertainment,etc.) 2. About the provider the provider owns off-the-shelf PB-level Large Language Model(LLM) Data, 3 million hours of speech data and 800TB of Imagery Data. These ready-to-go data supports instant delivery, quickly improve the accuracy of AI models. For more details, please visit us at https://www.the provider.ai/datasets/llm?source=the provider
Technical specifications
- Modalities
- Audio
- File formats
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Specifications: ‣ Volume: 100,000+ hours ‣ Format: 8kHz, mono channel (WAV audio + JSON transcript) ‣ Environment: Studio, podcast-quality recording ‣ Recording content:…
- Language
- Arabic
- Volume
- 10k h
- Domain
- Education +1
- Use case
- Speech recognition