Using RASTA in task independent TANDEM feature extraction

In this work, we investigate the use of RASTA filter in the TANDEM feature extraction method when trained with a task independent data. RASTA filter removes the linear distortion introduced by the communication channel which is demonstrated in a 18% relative improvement on the Numbers 95 task. Also, studies yielded a relative improvement of 35% over the basic PLP features by combining TANDEM features and conventional PLP features.

Related material


EPFL authors