Fine-Tune Whisper for Multilingual ASR with Hugging Face Transformers

AI Impact Summary

The guide provides a practical, Colab-friendly workflow to fine-tune OpenAI's Whisper on multilingual ASR data using Hugging Face Transformers and related libraries. It covers data preparation, feature extractor/tokenizer setup, training and evaluation, and demo deployment, and shows how to push checkpoints to the Hugging Face Hub for versioning. By using the multilingual Whisper checkpoints and Hindi data from Common Voice, it demonstrates end-to-end customization with as little as 8 hours of fine-tuning data, enabling teams to tailor ASR to low-resource languages.