Connectionist Temporal Classification with Maximum Entropy Regularization

Hu Liu, Sheng Jin, Changshui Zhang

Neural Information Processing Systems 

However, CTC tends to produce highly peaky and overconfident distributions, which is a symptom of overfitting. To remedy this, we propose a regularization method based on maximum conditional entropy which penalizes peaky distributions and encourages exploration.