The IBM 2016 English Conversational Telephone Speech Recognition System
Table 1: Word error rates for sigmoid vs. Maxout RNNs trained with annealed dropout on Hub5’00 after cross-entropy training (and sequence training for Maxout).
['Model', 'WER SWB', 'WER CH']
The decodings are done with a small vocabulary of 30K words and a small 4-gram language model with 4M n-grams. We observe that the maxout RNNs are consistently better and that, by themselves, they achieve a similar WER as our previous best model which was the joint RNN/CNN with sigmoid activations.