Africanvoice/African_voices_igbo

🇳🇬 WaZoBiaSpeech: 500+ Hour Igbo (ibo) Corpus

Version: Work-in-Progress — Last Updated 30 Nov 2025

NOTE: This dataset is not final. Updates, corrections, and expansions will continue through December 2025. Please check this repository regularly for the latest release. Do not benchmark or cite incomplete versions.

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🌍 Dataset Overview

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

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🛠️ 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

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💻 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("Data-Science-Nigeria/African_voices_igbo", "ibo", split="train")

# Load a specific split (e.g., development)
ds_dev = load_dataset("Data-Science-Nigeria/African_voices_igbo", "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(
    "Data-Science-Nigeria/African_voices_igbo", 
    "ibo", 
    split="dev_test", 
    streaming=True
)

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🚀 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

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⛔ 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

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⚖️ 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/Data-Science-Nigeria/African_voices_igbo},
  note    = {Igbo subset (ibo) version},
  type    = {dataset}
}

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📧 Contact & Support

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

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