Pseudo2Real: Task Arithmetic for Pseudo-Label Correction in Automatic Speech Recognition
The episode discusses 'Pseudo2Real,' a method for correcting pseudo-label errors in Automatic Speech Recognition (ASR) without needing target-domain ground truth. The authors use a correction vector learned from real labels to improve models trained on noisy pseudo-labels, achieving up to 35% relative Word Error Rate reduction on certain accents.