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Igbo Speech Dataset

The most comprehensive Igbo speech dataset on HuggingFace - natural, real-world Igbo from native speakers across Southeast Nigeria and the diaspora.

Dataset Overview

  • Total audio samples: 36 recordings
  • Total duration: ~22 minutes
  • Primary region: Nigeria (Owerri, Southeast Nigeria)
  • Context: Natural spontaneous speech (free_speech)
  • Audio format: WAV files
  • Sample rate: 48 kHz
  • License: CC BY-NC 4.0 (free for research, non-commercial use)

Language Context

Igbo (Asụsụ Igbo) is one of Nigeria's major languages:

  • Speakers: 45M+ (27M native, 18M+ L2)
  • Official language: Nigeria (one of 3 major languages alongside Hausa, Yoruba)
  • Geographic spread: Southeast Nigeria (Anambra, Imo, Abia, Enugu, Ebonyi states), diaspora
  • Writing system: Latin alphabet (standardized orthography)
  • Linguistic family: Niger-Congo (Volta-Niger branch)
  • Cultural significance: Igbo literature, music (highlife), Nollywood (Igbo films)
  • Digital presence: Growing on social media, YouTube, Nigerian tech ecosystem

Target Applications

This dataset is designed for:

  • Igbo ASR systems - Speech recognition for 45M+ speakers
  • Voice assistants - Nigerian tech startups, mobile banking in Southeast Nigeria
  • TTS for Igbo - Text-to-speech with authentic Igbo pronunciation
  • Language learning apps - Pronunciation training for Igbo learners
  • Content moderation - Social media platforms operating in Nigeria
  • Transcription services - Igbo films, radio, podcasts, Nollywood content
  • Cultural preservation - Digitizing Igbo oral traditions, proverbs (ilu)

Dataset Structure

igbo-speech/
└── data/
    ├── audio/              # 36 WAV files
    └── metadata.csv        # Speaker metadata & transcripts

Data Splits

Igbo (Nigeria)

  • Files: 36 recordings
  • Dialect: Primarily Owerri Igbo (Central Igbo, widely understood)
  • Context: Natural spontaneous speech
  • Use case: General-purpose Igbo ASR, Southeast Nigerian voice AI

Languages Sampled in This Dataset ✅

36 audio samples available for immediate download:

  • Igbo: 36 files (~22 minutes)

Full OTS Inventory Available 📊

This sample represents <0.21% of Silencio's complete Igbo speech inventory.

Contact us for access to our full Igbo corpus:

Igbo by Country:

  • Nigeria: 939 hours, 81,391 recordings
  • Angola: 4 hours, 366 recordings
  • United States: 3 hours, 286 recordings
  • United Kingdom: 2 hours, 145 recordings
  • American Samoa: 1 hour, 166 recordings
  • South Africa: 1 hour, 27 recordings
  • Ghana: 0.3 hours, 16 recordings
  • Algeria: 0.3 hours, 46 recordings
  • + 10 more countries (diaspora communities)

Total: 952+ hours across 83,000+ recordings

Contact us for access: sofia@silencioai.com

Key Features

Native speakers - Authentic Southeast Nigerian Igbo (Owerri dialect)
Natural speech - Real conversational Igbo, not scripted
Central dialect - Owerri variant (widely understood across Igboland)
Diverse topics - Daily life, business, opinions, culture
High audio quality - 48 kHz WAV format
Rich metadata - Gender, dialect, emotions, transcriptions in Latin script
Ethical data collection - Consent-based, privacy-preserving

Use Cases

1. Igbo Speech Recognition

Build ASR systems for the 45M+ Igbo-speaking market in Southeast Nigeria and the diaspora.

2. Voice Banking & Fintech

Power voice-enabled mobile banking in Southeast Nigeria (Owerri, Aba, Enugu, Onitsha).

3. Igbo TTS

Train text-to-speech models with authentic Igbo pronunciation and tonal patterns.

4. Content Moderation

Build speech detection for Nigerian social media platforms and Igbo content on YouTube/TikTok.

5. Nollywood & Media

Improve automatic transcription for Igbo films, radio shows, and podcasts.

6. Cultural Preservation

Digitize Igbo oral traditions, proverbs (ilu), folktales (akụkọ ifo), and highlife music.

Loading the Dataset

from datasets import load_dataset

# Load full Igbo dataset
dataset = load_dataset("SilencioNetwork/igbo-speech")

# Access samples
for sample in dataset['train']:
    audio = sample['audio']
    transcript = sample['transcript']
    dialect = sample['dialect']
    print(f"Transcript: {transcript}")
    print(f"Dialect: {dialect}")

Sample Metadata

Each recording includes:

  • file_name: Audio file path
  • id: Unique recording ID
  • gender: Speaker gender
  • location: Speaker location
  • mother_tongue: Native language (Igbo)
  • dialect: Regional variant (Nigeria - Owerri)
  • duration: Recording length (seconds)
  • emotions: Emotion labels (focused, relaxed, happy, etc.)
  • language: Igbo
  • type_of_script: free_speech (spontaneous, unscripted)
  • transcript: Whisper-generated transcription (Latin script)
  • script: Original prompt (question asked in Igbo)

Igbo Speech Characteristics

This dataset captures authentic Igbo speech features:

  • Tonal language: High, low, downstep tones - critical for word meaning
  • Vowel harmony: ATR (advanced tongue root) harmony system
  • Syllable structure: Primarily CV (consonant-vowel)
  • Nasal vowels: Distinctive nasalization (ụ, ọ, etc.)
  • Complex morphology: Rich verb affixation
  • Natural prosody: Authentic rhythm, stress, intonation
  • Real-world audio: Mobile recordings, natural environments

Market Context

Southeast Nigerian Economy

  • 45M+ Igbo speakers - One of Nigeria's 3 major language groups
  • Southeast Nigeria: 25M+ population, major commercial zone
  • Aba/Onitsha: Commercial hubs, major markets
  • Diaspora: Large Igbo communities in US, UK (high-value market)
  • Entrepreneurial culture: Igbo traders/business owners across West Africa
  • Nollywood: Igbo-language films popular across Nigeria
  • Highlife music: Igbo cultural tradition influencing African pop music

Why Igbo Matters

  • Underrepresented in AI: <0.01% of speech datasets despite 45M+ speakers
  • Commercial language: Southeast Nigeria's economy (manufacturing, trade)
  • Cultural influence: Igbo literature (Chinua Achebe, Chimamanda Adichie), music, film
  • Diaspora market: Wealthy communities in US/UK seeking language tech
  • Growing digital economy: E-commerce, fintech emerging in Aba/Onitsha/Nnewi

Igbo Dialects

Owerri Igbo (represented in this dataset) is part of Central Igbo:

  • Widely understood across Igboland
  • Used in some media and education
  • Mutually intelligible with other Central dialects

Standard Igbo (based on Owerri/Onitsha) is used in:

  • Education
  • Radio/TV broadcasts
  • Religious services
  • Written literature

Other major dialect groups: Onitsha, Nsukka, Owerri, Ngwa (all mutually intelligible)

Tonal Language Considerations

Igbo is a tonal language - pitch changes word meaning:

  • àkwá (crying)
  • ákwà (cloth)
  • ákwá (egg)
  • ákwà (bridge)

ASR/TTS systems need to capture these tone distinctions for accurate Igbo processing.

Ethical Considerations

All data was collected with explicit informed consent from native Igbo speakers. Recordings contain general conversational topics only - no sensitive personal information.

Comparison to Other Datasets

Dataset Language Hours Speakers Natural?
LibriSpeech English 1,000 2,484 ❌ Read speech
Common Voice Igbo ~5 Few ⚠️ Read sentences
Silencio Igbo Igbo 952+ 3,900+ ✅ Spontaneous

This is the largest natural Igbo speech dataset available.

Citation

If you use this dataset in your research or commercial product, please cite:

@dataset{silencio_igbo_speech_2026,
  title={Igbo Speech Dataset},
  author={Silencio Network},
  year={2026},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/SilencioNetwork/igbo-speech}
}

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License

CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0 International)

✅ Free for research and non-commercial use
❌ Commercial use requires licensing (contact us)

About Silencio

Silencio is a voice AI data sourcing company with 2M+ contributors across 180+ countries. We provide scaled sourcing of real-world audio and speech data for AI labs, robotics companies, and enterprises building voice AI products.

🌐 silencioai.com
📧 sofia@silencioai.com


Tags: igbo, asụsụ igbo, nigerian languages, west africa, nigeria, southeast nigeria, owerri, tonal language, african languages, low-resource languages, speech recognition, asr, tts, voice ai, natural speech, spontaneous speech, nigerian speech, nollywood

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