PASE+

2000년 도입 · 논문 2편에서 사용

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.

출처: Multi-task self-supervised learning for Robust Speech Recognition

소개 논문: Multi-task self-supervised learning for Robust Speech Recognition