Fiction Sentence Expansion and Enhancement via Focused Objective and Novelty Curve Sampling

Yuri Safovich, Amos Azaria

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

We describe the task of sentence expansion and enhancement, in which a sentence provided by a human is expanded in some creative way. The expansion should be understandable, believably grammatical, and highly related to the original sentence. Sentence expansion and enhancement may serve as an authoring tool, or integrate in dynamic media, conversational agents, and advertising. We implement a neural sentence expander, which is trained on sentence compressions generated from a corpus of modern fiction. We modify the objective loss function to support the task by focusing on new words, and decode at test time with controlled curve-like novelty sampling. We run the sentence expander on sentences provided by human subjects and have humans evaluate these expansions. The generation methods are shown to be comparable to, and as well liked as, subjects' original input sentences, and preferred over baselines.

Original languageEnglish
Title of host publicationProceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020
EditorsMiltos Alamaniotis, Shimei Pan
PublisherIEEE Computer Society
Pages835-843
Number of pages9
ISBN (Electronic)9781728192284
DOIs
StatePublished - Nov 2020
Event32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020 - Virtual, Baltimore, United States
Duration: 9 Nov 202011 Nov 2020

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2020-November
ISSN (Print)1082-3409

Conference

Conference32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020
Country/TerritoryUnited States
CityVirtual, Baltimore
Period9/11/2011/11/20

Keywords

  • NLP
  • Sentence Enhancement
  • Text Generation

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