InterAug: Augmenting Noisy Intermediate Predictions for CTC-based ASR
Journal: arXiv (Cornell University)
Year: 2022

This paper proposes InterAug: a novel training method for CTC-based ASR using augmented intermediate representations for conditioning. The proposed method exploits the conditioning framework of self-conditioned CTC to train robust models by conditioning with "noisy" intermediate predictions. During the training, intermediate predictions are changed to incorrect intermediate predictions, and fed into the next layer for conditioning. The subsequent layers are trained to correct the incorrect inter