Podcast Audio Data | Egyptian Arabic Multi-Speaker Dialogue Audio Corpus | 10,000+ Hours with Full Transcription | .WAV .JSON
Overview
Podcast Audio Data | Egyptian Arabic Multi-Speaker Dialogue Audio Corpus | 10,000+ Hours with Full Transcription | .WAV .JSON is a multimodal dataset. It covers Arabic. The provider states a volume of 10,000 hours. Typical applications include speech recognition, speaker recognition, LLM pre-training and 1 more. Relevant sectors: Education and AI & Machine Learning. The listing mentions transcription, timestamps and speaker labels. Pricing is not published and is provided on request.
Primary applications
What the listing offers
- Stated volume of 10k hours.
- Listing mentions transcription, timestamps, speaker labels.
Specifications: ‣ Volume: 100,000+ hours ‣ Format: 8kHz, mono channel (WAV audio + JSON transcript) ‣ Environment: Studio, podcast-quality recording ‣ Recording content: Fully natural conversation, topic-guided across education, entertainment, food, legal, and automotive domains ‣ Annotation: Speaker diarization, speaker ID, gender tags, timestamps, full transcription ‣ Accuracy: 98%+ word accuracy ‣ Language: Mandarin Chinese, English, Portuguese, Spanish, and more ‣ Application scenarios: Speech recognition; conversational AI; multilingual NLP ‣ Availability: Shelf-ready; additional volume, languages, or domain coverage available on request About the provider Data: 8+ years producing AI training data, podcast audio data, with 100+ in-house specialists across offices in Canada and China.
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Specifications: ‣ Volume: 100,000+ hours ‣ Format: 8kHz, mono channel (WAV audio + JSON transcript) ‣ Environment: Studio, podcast-quality recording, podcast audio data…
- Language
- —
- Volume
- 10k h
- Domain
- Education +1
- Use case
- Speech recognition