🇲🇱Mali

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.

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.