African-Whisper vs MALIBA-AI Bambara TTS

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.

MALIBA-AI Bambara TTS is a neural text-to-speech model for Bambara (Bamanankan), the most widely spoken language in Mali, built on the Spark-TTS framework with a Qwen2.5-based backbone of around 500M parameters. It supports 10 authentic Bambara speaker voices and outputs 16kHz mono audio without a separate vocoder. It is released under a non-commercial MALIBA-AI research license.