Research· 🧪 Worth Testing
Optimizing Whisper ASR Fine-Tuning via Smart Data Selection
Researchers have proposed an embedding-based k-center approach to select smaller, highly representative subsets of training data for Whisper fine-tuning. This method outperforms random sampling by capturing greater linguistic diversity, particularly effective when training budgets are limited.