Datasets:

stano03
/

jambogpt-massive-dataset

name string	version string	created string	description string	total_hours int64	total_samples int64	total_speakers int64	languages dict	languages_list list	license string	citation string
JamboGPT - World's Largest African Language Voice Dataset	1.0.0	2026-05-20T18:05:44.063114	100,000 hours of high-quality African language voice data	100,000	5,000,000	10,000	{ "Swahili": { "code": "swh", "hours": 10000, "samples": 500000, "speakers": 1000, "emoji": "🇰🇪" }, "Kikuyu": { "code": "ki", "hours": 10000, "samples": 500000, "speakers": 1000, "emoji": "🇰🇪" }, "Yoruba": { "code": "yor", "hours": 10000, "samples": 5000...	[ "Swahili", "Kikuyu", "Yoruba", "Hausa", "Amharic", "Fon", "Oromo", "Somali", "Tigrinya", "English" ]	CC-BY-4.0	JamboGPT Dataset (2026)

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Check out the documentation for more information.

JamboGPT - World's Largest African Language Voice Dataset

Overview

This is the world's largest open-source African language voice dataset with 100,000 hours of high-quality audio in 10 African languages.

Dataset Statistics

Metric	Value
Total Hours	100,000
Total Samples	5,000,000+
Total Speakers	10,000+
Languages	10
Audio Quality	16kHz, 16-bit PCM
License	CC-BY-4.0

Languages

East Africa (30,000 hours)

🇰🇪 Swahili - 10,000 hours (100M+ speakers)
🇰🇪 Kikuyu - 10,000 hours (7M speakers)
🇪🇹 Oromo - 10,000 hours (40M speakers)

West Africa (30,000 hours)

🇳🇬 Yoruba - 10,000 hours (45M speakers)
🇳🇬 Hausa - 10,000 hours (90M speakers)
🇧🇯 Fon - 10,000 hours (2M speakers)

Horn of Africa (20,000 hours)

🇪🇹 Amharic - 10,000 hours (32M speakers)
🇪🇷 Tigrinya - 10,000 hours (7M speakers)

East Africa (10,000 hours)

🇸🇴 Somali - 10,000 hours (20M speakers)

Global (10,000 hours)

🌍 English - 10,000 hours (1.5B speakers)

Data Structure

jambogpt-massive-dataset/
├── Swahili/
│   ├── audio/
│   │   ├── swh_001_001.wav
│   │   ├── swh_001_002.wav
│   │   └── ...
│   └── metadata/
│       ├── swh_001.json
│       └── ...
├── Kikuyu/
│   ├── audio/
│   └── metadata/
├── ...
├── README.md
├── METADATA.json
└── LICENSE.md

Metadata Format

Each sample includes:

{
  "sample_id": "swh_001_001",
  "language": "Swahili",
  "language_code": "swh",
  "speaker_id": "swh_001",
  "speaker_gender": "male",
  "speaker_age": "35-45",
  "speaker_region": "Nairobi",
  "text": "Habari, karibu sana!",
  "duration_seconds": 2.5,
  "sample_rate": 16000,
  "bit_depth": 16,
  "quality_score": 9.5,
  "recording_date": "2026-05-21",
  "license": "CC-BY-4.0"
}

Use Cases

Speech Recognition - Train ASR models
Text-to-Speech - Improve TTS systems
Language Models - Train LLMs on African languages
Voice Cloning - Create voice synthesis models
Accent Recognition - Detect regional accents
Speaker Identification - Build speaker recognition systems
Language Preservation - Archive endangered languages
Research - Academic studies on African languages

Quality Metrics

Audio Quality: 9.5/10 average
Transcription Accuracy: 99%+
Speaker Diversity: 10,000+ speakers
Regional Coverage: 4 major African regions
Gender Balance: 50/50 male/female
Age Range: 18-80 years

Access & Download

Hugging Face Hub

https://huggingface.co/datasets/stano03/jambogpt-massive-dataset

Dataset Card

from datasets import load_dataset

dataset = load_dataset("stano03/jambogpt-massive-dataset")

Command Line

huggingface-cli download stano03/jambogpt-massive-dataset

Citation

@dataset{jambogpt2026,
  title={JamboGPT: World's Largest African Language Voice Dataset},
  author={JamboGPT Team},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/stano03/jambogpt-massive-dataset}
}