Differentiable Pooling for Unsupervised Acoustic Model Adaptation
TABLE I: Baseline WER(%) results on selected test sets of our benchmark corpora
['[EMPTY]', 'TED', 'AMI', 'SWBD']
The Diff-Gauss and Diff-L2/ Diff-Lp models have comparable WERs, with a small preference towards Diff-Lp in terms of the final WER on TED and AMI; all have lower average WER than the baseline DNN. The gap between the pooled models increases on AMI data where Diff-Lp has a substantially lower WER (3.2% relative) than the fixed order Diff-L2 which is in turn has a lower WER than the other two models (Diff-Gauss and baseline DNN) by 2.1% relative.