Since the bigram language model of the NCM is trained on this corpus, we cannot directly use Switchboard to build LSTM LMs. The reason is that if the training data of Switchboard is used both for predicting language fluency and optimizing the loss function, the reranker will overestimate the model-based features 1-2. forward & backward LSTM LM scores 3-7. This is because the fluent sentence itself is part of the language model <cite>(Zwarts and Johnson, 2011)</cite> .