Creative Help: A Story Writing Assistant

Linguistic Features of Helpfulness in Automated Support for Creative Writing

“…Once one minute has elapsed since the author last edited the sentence, the application logs the modified sentence alongside its original version. See Roemmele and Gordon (2015) for further details about this tracking and logging functionality. The result of authors' interactions with the application is a dataset aligning generated suggestions to their corresponding modifications along with the story context that precedes the help request.…”

“…One such application focuses on providing automated support to human authors for story writing. In particular, Roemmele and Gordon (2015), Khalifa et al (2017), Manjavacas et al (2017), and Clark et al (2018) have developed systems that automatically generate suggestions for new sentences to continue an ongoing story.…”

“…In this work, we analyze a set of user interactions with the application Creative Help (Roemmele and Gordon, 2015), where users make 'help' requests to automatically suggest new sentences in a story, which they can then freely modify. We take advantage of Creative Help's functionality that tracks authors' edits to generated sentences, resulting in an alignment between each original suggestion and its modified form.…”

Proceedings of the Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2017)

“…Roemelle and Gordon offer a more hands on approach to assistive writing. Their system acts as a 'Narrative Auto-Completion', where the writer is prompted with possible sentences (Roemmele and Gordon, 2015). Though straightforward, this approach is highly intuitive and unobtrusive; however, the system risks fulfilling the role of tool rather than 31 collaborator.…”

Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics

“…Most story generation research has focused on modeling the plot, characters, and primary action of the story, using simplistic methods for producing the actual linguistic form of the stories (Turner, 1993;Riedl and Young, 2010). More recent work learns from data how to generate stories holistically without a clear separation between content selection and surface realization (McIntyre and Lapata, 2009), with a few recent methods based on recurrent neural networks (Roemmele and Gordon, 2015;. We follow the latter style and focus on a setting in which a few sentences of a story are provided (the context) and the task is to generate the next sentence in the story (the continuation).…”