@inproceedings{rosa-etal-2022-gpt,
title = "{GPT}-2-based Human-in-the-loop Theatre Play Script Generation",
author = "Rosa, Rudolf and
Schmidtov{\'a}, Patr{\'\i}cia and
Du{\v{s}}ek, Ond{\v{r}}ej and
Musil, Tom{\'a}{\v{s}} and
Mare{\v{c}}ek, David and
Obaid, Saad and
Nov{\'a}kov{\'a}, Marie and
Voseck{\'a}, Kl{\'a}ra and
Dole{\v{z}}al, Josef",
editor = "Clark, Elizabeth and
Brahman, Faeze and
Iyyer, Mohit",
booktitle = "Proceedings of the 4th Workshop of Narrative Understanding (WNU2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wnu-1.4",
doi = "10.18653/v1/2022.wnu-1.4",
pages = "29--37",
abstract = "We experiment with adapting generative language models for the generation of long coherent narratives in the form of theatre plays. Since fully automatic generation of whole plays is not currently feasible, we created an interactive tool that allows a human user to steer the generation somewhat while minimizing intervention. We pursue two approaches to long-text generation: a flat generation with summarization of context, and a hierarchical text-to-text two-stage approach, where a synopsis is generated first and then used to condition generation of the final script. Our preliminary results and discussions with theatre professionals show improvements over vanilla language model generation, but also identify important limitations of our approach.",
}
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%0 Conference Proceedings
%T GPT-2-based Human-in-the-loop Theatre Play Script Generation
%A Rosa, Rudolf
%A Schmidtová, Patrícia
%A Dušek, Ondřej
%A Musil, Tomáš
%A Mareček, David
%A Obaid, Saad
%A Nováková, Marie
%A Vosecká, Klára
%A Doležal, Josef
%Y Clark, Elizabeth
%Y Brahman, Faeze
%Y Iyyer, Mohit
%S Proceedings of the 4th Workshop of Narrative Understanding (WNU2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F rosa-etal-2022-gpt
%X We experiment with adapting generative language models for the generation of long coherent narratives in the form of theatre plays. Since fully automatic generation of whole plays is not currently feasible, we created an interactive tool that allows a human user to steer the generation somewhat while minimizing intervention. We pursue two approaches to long-text generation: a flat generation with summarization of context, and a hierarchical text-to-text two-stage approach, where a synopsis is generated first and then used to condition generation of the final script. Our preliminary results and discussions with theatre professionals show improvements over vanilla language model generation, but also identify important limitations of our approach.
%R 10.18653/v1/2022.wnu-1.4
%U https://aclanthology.org/2022.wnu-1.4
%U https://doi.org/10.18653/v1/2022.wnu-1.4
%P 29-37
Markdown (Informal)
[GPT-2-based Human-in-the-loop Theatre Play Script Generation](https://aclanthology.org/2022.wnu-1.4) (Rosa et al., WNU 2022)
ACL
- Rudolf Rosa, Patrícia Schmidtová, Ondřej Dušek, Tomáš Musil, David Mareček, Saad Obaid, Marie Nováková, Klára Vosecká, and Josef Doležal. 2022. GPT-2-based Human-in-the-loop Theatre Play Script Generation. In Proceedings of the 4th Workshop of Narrative Understanding (WNU2022), pages 29–37, Seattle, United States. Association for Computational Linguistics.