PASE+
Problem Agnostic Speech Encoder +
**PASE+** is a problem-agnostic speech encoder that combines a convolutional encoder followed by multiple neural networks, called workers, tasked to solve self-supervised problems (i.e., ones that do not require manual annotations as ground truth). An online speech distortion module is employed, that contaminates the input signals with a variety of random disturbances. A revised encoder is also proposed that better learns short- and long-term speech dynamics with an efficient combination of recurrent and convolutional networks. Finally, the authors refine the set of workers used in self-supervision to encourage better cooperation.
Multi-task self-supervised learning for Robust Speech Recognition
https://paperswithcode.com/paper/multi-task-self-supervised-learning-for-1
Multi-task self-supervised learning for Robust Speech Recognition