--- library_name: peft base_model: openai/whisper-large-v2 tags: - generated_from_trainer - multilingual - ASR - Open-Source language: - wo - fr - en model-index: - name: whosper-large results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Test Set type: custom split: test args: language: wo metrics: - name: Test WER type: wer value: 24.23 - name: Test CER type: cer value: 11.35 pipeline_tag: automatic-speech-recognition new_version: sudoping01/whosper-large-v3 --- # Whosper-large ## Model Overview Whosper-large is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) optimized for Wolof speech recognition Senegal's primary language, while maintaining strong multilingual capabilities. Built on OpenAI's Whisper-large-v2, it advances African language processing with notable improvements in Word Error Rate (WER) and Character Error Rate (CER). Whether you're transcribing conversations, building language learning tools, or conducting research, this model is designed for researchers, developers, and students working with Wolof speech data. ### Key Strengths - **Strong Multilingual**: Excellent performance in Wolof, French, and English - **Code-Switching**: Handles natural language mixing, especially Wolof-French - **Consistent Results**: Maintains quality across different languages - **Open Source**: Released under the [apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) license - **African NLP**: Supporting African language technology development ## Performance Metrics - **WER**: 0.2423 - **CER**: 0.1135 ## Key Features - Strong multilingual performance (Wolof, French, English) - Excellent performance on code-switched content - Consistent performance across different languages ## Limitations - Outputs in lowercase only - Limited punctuation support - Low performances on bad quality audios ## Training Data Trained on diverse Wolof speech data: - **ALFFA Public Dataset** - **FLEURS Dataset** - **Bus Urbain Dataset** - **Kallama Dataset** ## Quick Start Guide ### Installation ```bash pip install git+https://github.com/sudoping01/whosper.git@v1.0.0 ``` ### Basic Usage ```python from whosper import WhosperTranscriber # Initialize the transcriber transcriber = WhosperTranscriber(model_id="CAYTU/whosper-large") # Transcribe an audio file result = transcriber.transcribe_audio("path/to/your/audio.wav") print(result) ``` ### Training Results | Training Loss | Epoch | Step | Validation Loss | |---------------|-------|------|-----------------| | 3.0514 | 1.0 | 1732 | 0.6824 | | 2.2658 | 2.0 | 3464 | 0.5998 | | 2.0274 | 3.0 | 5196 | 0.5282 | | 1.48 | 4.0 | 6928 | 0.4793 | | 1.1693 | 5.0 | 8660 | 0.4441 | | 0.8762 | 5.9970 | 10386 | 0.4371 | ## Framework Versions - PEFT: 0.14.1.dev0 - Transformers: 4.48.0.dev0 - PyTorch: 2.5.1+cu124 - Datasets: 3.2.0 - Tokenizers: 0.21.0 ## Contributing to African NLP Whosper-large embodies our commitment to open science and the advancement of African language technologies. We believe that by making cutting-edge speech recognition models freely available, we can accelerate NLP development across Africa. Join our mission to democratize AI technology: - **Open Science**: Use and build upon our research - all code, models, and documentation are open source - **Research Collaboration**: Integrate Whosper into your research projects and share your findings - **Community Building**: Help us create resources for African language processing - **Educational Impact**: Use Whosper in educational settings to train the next generation of African AI researchers ## License [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0) This model is released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0) to encourage research, commercial use, and innovation in African language technologies while ensuring proper attribution and patent protection. ## Citation ```bibtex @misc{whosper2025, title={Whosper-large: A Multilingual ASR Model for Wolof with Enhanced Code-Switching Capabilities}, author={Seydou DIALLO}, year={2025}, publisher={Hugging Face}, url={https://huggingface.co/CAYTU/whosper-large}, version={1.0} } ``` ## Acknowledgments Developed by [Seydou DIALLO](https://www.linkedin.com/in/seydou-diallo-08ab311ba) at [Caytu Robotics](https://caytu.ai)'s AI Department, building on OpenAI's [Whisper-large-v2](https://huggingface.co/openai/whisper-large-v2). Special thanks to the Wolof-speaking community and contributors advancing African language technology. ## Contact US For any question or support contact us Email : sdiallo@caytu.com