Pruning Whisper Encoders via Leave-One-Layer-Out WER Analysis

This method reduces Whisper encoder size by 18.5% by removing the six layers that cause the least change in Word Error Rate (WER). The approach enables more efficient ASR without requiring the extensive custom inference implementations typical of other pruning methods.