Learning Neural Trans-Dimensional Random Field Language Models with Noise-Contrastive Estimation
Learning Neural Trans-Dimensional Random Field Language Models with Noise-Contrastive Estimation
Trans-dimensional random field language models (TRF LMs) where sentences are modeled as a collection of random fields, have shown close performance with LSTM LMs in speech recognition and are computationally more efficient in inference. However, the training efficiency of neural TRF LMs is not satisfactory, which limits the scalability of …