END-TO-END NEURAL SEGMENTAL MODELS FOR SPEECH RECOGNITION
TABLE II: PERs (%) for segmental models trained in multiple stages with feature encoders pretrained with the frame-wise cross entropy or the CTC loss. Two-stage training is denoted 2s, and two-stage training followed by fine-tuning is denoted 2s+ft.
['[EMPTY]', 'frame loss 2s', 'frame loss 2s+ft', 'frame loss 2s+ft', 'CTC 2s', 'CTC 2s+ft', 'CTC 2s+ft']
After fixing the weight function to the SRNN, we compare encoders pretrained with the frame-wise cross entropy and with the CTC loss. It is clear that for all losses, using the encoder pretrained with the CTC loss leads to better performance.