A state-of-the-art automatic speech recognition (ASR) model for the Hausa language, fine-tuned on Whisper Small architecture. This model was powered by Awarri Technologies and an initiative of the The Federal Ministry of Communications, Innovation and Digital Economy to advance indigenous language technologies and promote digital inclusion.
Model Description
Model Name: Hausa-ASR-v1.0
Architecture: Whisper Small (244M parameters)
Language: Hausa (ha)
License: [Other]
Model Size: ~244M parameters
Training Data
Training Time: 120 hours
Data Sources:
Langeasy platform recordings from speakers across Nigeria's 6 geopolitical zones
Publicly available datasets
Geographic Coverage: All 6 geopolitical zones of Nigeria
Quick Start
Installation
pip install torch torchaudio transformers librosa
Basic Usage
python
1from transformers import pipeline
2import librosa
34# Initialize the ASR pipeline5asr = pipeline("automatic-speech-recognition", model="NCAIR1/Hausa-ASR")67# Load audio file (16kHz recommended)8audio, sr = librosa.load("your_hausa_audio.wav", sr=16000)910# Transcribe11result = asr(audio)12print(result["text"])
Advanced Usage
python
1from transformers import WhisperProcessor, WhisperForConditionalGeneration
2import torch
3import librosa
45# Load model and processor6processor = WhisperProcessor.from_pretrained("NCAIR-NG/Hausa")7model = WhisperForConditionalGeneration.from_pretrained("NCAIR1/Hausa-ASR")89# Process audio10audio, sr = librosa.load("audio_file.wav", sr=16000)11input_features = processor(audio, sampling_rate=sr, return_tensors="pt").input_features
1213# Generate transcription14with torch.no_grad():15 predicted_ids = model.generate(input_features)16 transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)1718print(transcription[0])
Use Cases
✅ Recommended Applications
Academic research on Hausa linguistics
Educational tools for Hausa language learning
Accessibility applications for hearing-impaired Hausa speakers
Cultural preservation and documentation
Voice-enabled applications for Hausa speakers
Media and broadcast transcription
Government services requiring Hausa language support
❌ Not Recommended
Mass surveillance or unauthorized monitoring
High-stakes applications without human oversight (legal, medical)
Applications that could discriminate based on dialectal variations
Limitations
Dialectal Coverage: Some regional dialects may have varying accuracy levels
Code-Switching: Reduced performance when mixing Hausa with English
Audio Quality: Performance degrades with poor audio quality or excessive noise
Children's Speech: Limited training data for younger speakers
Domain-Specific Content: May require fine-tuning for specialized domains
Model Details
Technical Specifications
Architecture: Transformer-based (Whisper Small)
Parameters: 244M
Input: Audio waveform (16kHz recommended)
Output: Hausa text transcription
Context Length: 30 seconds maximum per inference
Training Details
Base Model: OpenAI Whisper Small
Fine-tuning Framework: PyTorch with Hugging Face Transformers
Geographic Representation: All 6 geopolitical zones of Nigeria
Training Duration: 120 hours
Fine-tuning
For domain-specific applications, this model can be further fine-tuned:
python
1from transformers import WhisperForConditionalGeneration, Seq2SeqTrainer
23# Load base model4model = WhisperForConditionalGeneration.from_pretrained("NCAIR1/Hausa-ASR")56# Fine-tune with your domain-specific Hausa data7# Recommended: 10-20 hours of high-quality domain audio
Ethical Considerations
Designed to promote equitable access to speech technology for Hausa speakers
Users should consider cultural sensitivity when deploying the model
Continuous monitoring for bias and performance variations is recommended
Should not be used for surveillance or applications that could harm individuals
Citation
bibtex
1@misc{awarri2025hausa,
2 title={Hausa-ASR-v1.0: Automatic Speech Recognition for Hausa Language},
3 author={Awarri Technologies},
4 year={2025},
5 howpublished={Hugging Face Model Hub},
6 url={https://huggingface.co/NCAIR1/Hausa-ASR}
7}
Contact & Support
Initiative Of: The Federal Ministry of Communications, Innovation and Digital Economy
Powered By: Awarri Technologies
Project: N-ATLaS
Version: 1.0 (September 2025)
For issues, questions, or collaboration opportunities, please refer to the model repository discussions or contact Awarri Technologies.
Acknowledgments
This work was made possible through:
Federal Government Of Nigeria
AWARRI Technologies
National Information Technology Development Agency (NITDA)
The Federal Ministry of Communications, Innovation and Digital Economy
National Center for Artificial Intelligence and Robotics
Data contributors from across Nigeria's 6 geopolitical zones via the Langeasy platform
The broader Nigerian language technology research community
Terms of Use for Hausa-ASR
Effective Date: September 2025 Version: 1.0
1. Introduction & Scope
Awarri Technologies, in partnership with the Federal Government of Nigeria, hereby releases Hausa-ASR, an Automatic Speech Recognition (ASR) model for the Hausa language, based on the Whisper Small architecture. This model is one of the components of N-ATLaS (Nigeria – Automatic Transcription and Language Systems).
Hausa-ASR is released under an Open-Source Research and Innovation License inspired by permissive licenses such as Apache 2.0 and MIT, but with additional restrictions tailored for responsible use in Nigeria and globally.
The model is intended to support:
Research and academic study
Education and capacity development
Civic technology and accessibility initiatives
Linguistic and cultural preservation, and community projects
⚠️ Hausa-ASR is not an enterprise-grade or commercial system. Commercial or large-scale enterprise use requires a separate licensing agreement (see Section 3).
2. License Grant
Subject to compliance with these Terms, users are granted a worldwide, royalty-free, non-exclusive, non-transferable license to:
Download, use, and run Hausa-ASR for permitted purposes
Modify, adapt, and create derivative works of Hausa-ASR
Redistribute Hausa-ASR and derivative works under these same Terms
Conditions:
Attribution must be given to:
“Awarri Technologies and the Federal Government of Nigeria, developers of N-ATLaS (Hausa-ASR).”
Derivative works must be released under the same license, ensuring consistency and traceability.
If Hausa-ASR or its derivatives are renamed, they must carry the suffix: “Powered by Awarri.”
3. User License Cap (1000 Users)
Use of Hausa-ASR is limited to organizations, institutions, or projects with no more than 1000 active end-users.
An active end-user is an individual who directly interacts with Hausa-ASR outputs (e.g., via an app, website, or integrated service) within a rolling 30-day period.
Organizations exceeding the 1000-user cap must obtain a commercial license directly from Awarri Technologies in partnership with the Federal Ministry of Communications, Innovation, and Digital Economy.
4. Acceptable Use
✅ Permitted Use Cases include (but are not limited to):
Academic and non-profit research
Accessibility for persons with disabilities
Language and cultural preservation projects
Civic technology and public benefit applications
Education, training, and community innovation
❌ Prohibited Use Cases include (but are not limited to):
Surveillance or unlawful monitoring
Discriminatory profiling or exclusionary practices
Disinformation, impersonation, or synthetic fraud
Military, intelligence, or weaponized deployment
Exploitative, harmful, or unlawful applications
5. Limitations & Disclaimer
Hausa-ASR is released “as-is”, without warranties of any kind, express or implied.
Known limitations include:
Dialectal coverage: Some regional dialects of Hausa may have varying accuracy levels
Code-switching: Reduced performance when mixing Hausa with English or other languages
Audio quality: Performance degrades with poor audio or excessive background noise
Children’s speech: Limited training data for younger speakers
Neither Awarri Technologies nor the Federal Government of Nigeria shall be liable for damages arising from the use of Hausa-ASR.
6. Ethical & Cultural Considerations
Users must:
Respect Nigeria’s cultural and linguistic diversity, particularly within Hausa-speaking communities
Ensure transparent reporting of accuracy, bias, and limitations
Uphold human rights and privacy standards in all deployments
7. Data & Privacy
All training data used in Hausa-ASR was either publicly available or government-approved for use.
Users are strictly prohibited from using Hausa-ASR for unauthorized personal data scraping, collection, or profiling.
8. Governance & Updates
Governance and oversight are led by the Federal Ministry of Communications, Innovation, and Digital Economy, in collaboration with the National Centre for Artificial Intelligence & Robotics (NCAIR).
Awarri Technologies shall act as the technical maintainer and custodian of Hausa-ASR.
Updates, improvements, and community contributions will be published periodically.
Users must comply with the specific Terms attached to each version release.
9. Legal & Jurisdiction
These Terms are governed by the laws of the Federal Republic of Nigeria.
In the event of a dispute, parties agree to seek resolution first through mediation under the auspices of the Federal Ministry of Justice, before pursuing litigation in Nigerian courts.
10. Termination
The Federal Government of Nigeria and Awarri Technologies reserve the right to revoke, suspend, or terminate usage rights if these Terms are violated.
Termination may apply to individual users, institutions, or organizations found in breach.
11. Contact & Attribution
For licensing, inquiries, and commercial partnerships regarding Hausa-ASR, contact:
