Recurrent neural network-based language modeling for an automatic Russian speech recognition system

In the paper, we describe a research of recurrent neural network language models for N-best list rescoring for automatic continuous Russian speech recognition. We tried recurrent neural networks with different number of units in the hidden layer. We achieved the relative word error rate reduction of 14% with respect to the baseline 3-gram model.