InspireMe: Learning Sequence Models for Stories

 

We present a novel approach to modeling stories using recurrent neural networks.

February 4, 2018
30th Conference on Innovative Applications of Artificial Intelligence (IAAI-18) 2018

 

Authors

Vincent Fortuin (Disney Research/ETH Zurich)

Romann M. Weber (Disney Research)

Sasha Schriber (Disney Research)

Diana Wotruba (Disney Research)

Markus Gross (Disney Research/ETH Zurich)

InspireMe: Learning Sequence Models for Stories

Abstract

We present a novel approach to modeling stories using recurrent neural networks. Different story features are extracted using natural language processing techniques and used to encode the stories as sequences. These sequences can be learned by deep neural networks, in order to predict the next story events. The predictions can be used as an inspiration for writers who experience a writer’s block. We show that suggestions from our model are rated as highly as the real scenes from a set of films and that our visualizations can help people in gaining deeper story understanding.

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