English Conversational Telephone Speech Recognition by Humans and Machines
Table 7: Word error rates for LSTMs and ResNet and frame-level score fusion results across all testsets (36M n-gram LM).
['Model', 'SWB', 'CH', 'RT’02', 'RT’03', 'RT’04', 'DEV’04f']
All decodings are done with an 85K word vocabulary and a 4-gram language model with 36M n-grams. We note that LSTMs and ResNets exhibit a strong complementarity which improves the WER for all testsets.