African-Whisper vs Bambara-ASR-v2

An open-source framework (PyPI: africanwhisper) for fine-tuning OpenAI's Whisper on multilingual African-language audio datasets such as Common Voice and FLEURS, with optimized inference, diarization and deployment. Created by Kevin Kibe.

Bambara-ASR-v2 is an automatic speech recognition model for Bambara (Bamanankan) fine-tuned from OpenAI's Whisper-large-v2 using parameter-efficient tuning, reaching about 25 percent word error rate. It handles natural Bambara-French code-switching common in Mali's multilingual context. It is released under Apache 2.0 as part of the MALIBA-AI community initiative.