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Dataset Description
Dialectra Yoruba Speech Corpus v1 is an open speech dataset collected from native Yoruba speakers across multiple regions and dialect communities.
The dataset was created to support the development of speech technologies for Yoruba, including Automatic Speech Recognition (ASR), Speech-to-Text (STT), Text-to-Speech (TTS), dialect research, and broader language technology applications.
This release contains transcribed speech recordings collected and verified through Dialectra's speech data platform.
Motivation
Despite being spoken by tens of millions of people across Nigeria and the global diaspora, Yoruba remains underrepresented in modern speech AI systems.
Dialectra was established to build dialect-aware speech infrastructure for African languages through:
- Speech collection
- Annotation
- Human verification
- Benchmarking
- Dialect evaluation
- Conversational speech infrastructure
This dataset is part of that mission.
Dataset Summary
| Metric | Value |
|---|---|
| Language | Yoruba |
| Country | Nigeria |
| Audio Format | WAV |
| Sampling Rate | 16 kHz |
| Dataset Version | v1 |
| Speakers | 41 |
| Audio Samples | 310 |
| Duration | 40 minutes + |
| Collection Method | Dialectra platform |
Dialect Coverage
The dataset includes recordings from Yoruba speakers across different regions.
Examples include:
- Standard Yoruba
- Oyo
- Ibadan
- Ijebu
- Ekiti
- Ondo
- Mixed Yoruba variants
Dialect representation may not be perfectly balanced.
Researchers are encouraged to evaluate model performance across dialect groups independently.
Data Collection Process
Speech samples were collected through the Dialectra platform.
Contributors voluntarily participated and recorded speech tasks using mobile and web interfaces.
Collection methods included:
- Scripted speech
- Prompt-based recordings
- Read speech
All contributors agreed to the platform's contribution and licensing terms.
Intended Uses
Suitable For
- Automatic Speech Recognition (ASR)
- Speech-to-Text (STT)
- Text-to-Speech (TTS)
- Dialect Classification
- Speech Research
- Acoustic Modeling
- Language Technology Development
Out-of-Scope Uses
- Speaker Identification
- Biometric Authentication
- Demographic Profiling
- Surveillance Applications
Benchmarking
Dialectra maintains internal benchmarking pipelines for evaluating speech quality and transcription accuracy.
Metrics may include:
- Word Error Rate (WER)
- Character Error Rate (CER)
- Dialect Recognition Rate (DRR)
- Dataset Coverage
Benchmark reports may be released separately.
Ethical Considerations
Researchers should consider:
- Dialect representation imbalance
- Regional variation
- Demographic coverage
- Potential biases within speech data
The dataset should be used responsibly and in compliance with applicable laws and regulations.
License
CC-BY-4.0
Citation
@dataset{dialectra_yoruba_2026, title={Dialectra Yoruba Speech Corpus v1}, author={Dialectra}, year={2026}, publisher={Hugging Face} }
About Dialectra
Dialectra is building dialect-aware speech infrastructure for African languages through speech collection, annotation, benchmarking, conversational datasets, and speech intelligence systems.
Website: https://dialectra.io
Contact: bakaka@dialectra.io
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