We consider the task of generative dialogue modeling for movie scripts. To this end, we extend the recently proposed hierarchical recurrent encoder decoder neural network and demonstrate that this model is competitive with state-of-the-art neural language models and backoff n-gram models. We show that its performance can be improved considerably by bootstrapping the learning from a larger questionanswer pair corpus and from pretrained word embeddings.
Specif-ically, in REF they constructed a generative model for movie dialogues based on a hierarchical recurrent encoder decoder neural network.
Hierarchical Neural Network Generative Models for Movie Dialogues.
ArXiv
ArXiv
Computer Science