Automated story generation is the problem of automatically selecting a sequence of events, actions, or words that can be told as a story. We seek to develop a system that can generate stories by learning everything it needs to know from textual story corpora. To date, recurrent neural networks that learn language models at character, word, or sentence levels have had little success generating coherent stories. We explore the question of event representations that provide a mid-level of abstraction between words and sentences in order to retain the semantic information of the original data while minimizing event sparsity. We present a technique for preprocessing textual story data into event sequences. We then present a technique for automated story generation whereby we decompose the problem into the generation of successive events (event2event) and the generation of natural language sentences from events (event2sentence). We give empirical results comparing different event representations and their effects on event successor generation and the translation of events to natural language.
|Title of host publication||32nd AAAI Conference on Artificial Intelligence, AAAI 2018|
|Number of pages||8|
|State||Published - 2018|
|Event||32nd AAAI Conference on Artificial Intelligence, AAAI 2018 - New Orleans, United States|
Duration: Feb 2 2018 → Feb 7 2018
|Name||32nd AAAI Conference on Artificial Intelligence, AAAI 2018|
|Conference||32nd AAAI Conference on Artificial Intelligence, AAAI 2018|
|Period||2/2/18 → 2/7/18|
Bibliographical noteFunding Information:
This work is supported by DARPA W911NF-15-C-0246. The views, opinions, and/or conclusions contained in this paper are those of the authors and should not be interpreted as representing the official views or policies, either expressed or implied of the DARPA or the DoD. The authors would like to thank Murtaza Dhuliawala, Animesh Mehta, and Yuval Pinter for technical contributions.
Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
ASJC Scopus subject areas
- Artificial Intelligence