WaZoBiaSpeech is a large-scale, high-quality, fully transcribed speech dataset for Igbo (ibo). This corpus is designed to accelerate the development of speech technology in African contexts, promoting linguistic diversity and supporting low-resource machine learning research.

The data includes both scripted and unscripted recordings collected through ethical, community-centered processes with broad demographic coverage.

Current Language Coverage: Igbo (ibo)

Language	Total Clips	Total Hours	Speakers
Igbo	150,434	504.92 h	527

🛠️ Dataset Structure and Features

The dataset is provided with the following features:

Field	Type	Description
`audio_id`	`string`	Unique audio identifier
`speaker_id`	`string`	Pseudonymized speaker code
`audio_path`	`Audio`	48 kHz mono WAV audio file
`transcript`	`string`	Clean human transcription
`duration_seconds`	`float64`	Duration of the audio clip in seconds
`gender`	`string`	Male / Female
`age_group`	`string`	Demographic band (15–29, 30–45, 46–60, 60+)
`education`	`string`	Primary, Secondary, Tertiary
`domain`	`string`	Context of the content (EV, HE, AG, BU)
`type`	`string`	Scripted / Unscripted
`split`	`string`	train / dev / dev_test (speaker-disjoint)
`language`	`string`	Language code (e.g., ibo)

Summary Statistics (Igbo)

Total Clips: 150,434
Total Hours: 504.92 h
Gender Split: 28.3% Male / 71.7% Female

💻 Loading the Dataset (Hugging Face)

The dataset is configured for easy loading of the Igbo (ibo) subset.

Recommended Environment

pip install --upgrade datasets[audio]
pip install --upgrade ffmpeg ffmpeg-python

Standard Load

from datasets import load_dataset

# Load the full training split
ds = load_dataset("Africanvoice/igbo_african_voice", "ibo", split="train")

# Load a specific split (e.g., development)
ds_dev = load_dataset("Africanvoice/igbo_african_voice", "ibo", split="dev")

Streaming Mode (for memory efficiency)

from datasets import load_dataset

# Load the dev_test split in streaming mode
ds_stream = load_dataset(
    "Africanvoice/igbo_african_voice", 
    "ibo", 
    split="dev_test", 
    streaming=True
)

🚀 Intended Use & Applications

This dataset is specifically designed for the following purposes:

Automatic Speech Recognition (ASR) Training
NLP for low-resource African languages
Cross-lingual learning and transfer learning research
Evaluation of multilingual ASR systems
Linguistic research and accent/dialect modeling

⛔ Use Restrictions & Limitations

To protect speaker privacy and prevent potential voice misuse, the following uses are strictly enforced:

Strictly Prohibited Uses 🛑

Voice cloning or adaptation (Text-to-Speech/TTS)
Voice biometrics, speaker identification, or mimicry
Surveillance, profiling, or any commercial application that relies on identifying or imitating individuals

Limitations ⚠️

Regional accent variation, while broad, is not entirely exhaustive
Spontaneous (unscripted) speech segments may include natural, low-level background noise
Not suitable for biometric or forensic use

⚖️ License and Citation

License

This dataset is released under the Creative Commons Attribution 4.0 (CC BY 4.0) license.

Citation

@dataset{wazobiaspeech-2025,
  title   = {WaZoBiaSpeech: A 2,500-Hour Multilingual Speech Corpus for Hausa, Igbo, Nigerian Pidgin, and Yoruba},
  author  = {EqualyzAI and African Voices Team},
  year    = {2025},
  url     = {https://huggingface.co/datasets/Africanvoice/igbo_african_voice},
  note    = {Igbo subset (ibo) version},
  type    = {dataset}
}

📧 Contact & Support

For questions, issues, or collaboration inquiries, please open an issue on the repository or contact the maintainers directly.

Last Updated: November 30, 2025
Maintainer: Data Science Nigeria / EqualyzAI

Downloads last month: 1,643

Total file size:

157 GB