Fine-Tuning Whisper for Automatic Speech Recognition in Baniwa: A Preliminary Study
Teaching AI to understand an endangered indigenous language with minimal data
Researchers adapted Whisper, an AI speech recognition system, to recognize Baniwa, an indigenous language spoken across Brazil, Colombia, and Venezuela with very few digital recordings. Using just 32 minutes of transcribed audio, the system correctly identified about 6 in 10 words — the first baseline for Baniwa speech recognition and proof that multilingual AI models can work with extremely limited training data.
Indigenous languages like Baniwa are disappearing as fewer people speak them, and digital tools almost never exist for them because companies focus on major languages. This work shows that endangered language communities don't need massive datasets to build functional speech recognition tools—they can leverage existing AI systems trained on major languages. This creates a practical pathway for documenting and preserving languages that otherwise leave no digital record.