@inproceedings{uthus-etal-2022-augmenting,
title = "Augmenting Poetry Composition with {V}erse by {V}erse",
author = "Uthus, David and
Voitovich, Maria and
Mical, R.J.",
editor = "Loukina, Anastassia and
Gangadharaiah, Rashmi and
Min, Bonan",
booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track",
month = jul,
year = "2022",
address = "Hybrid: Seattle, Washington + Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.naacl-industry.3",
doi = "10.18653/v1/2022.naacl-industry.3",
pages = "18--26",
abstract = "We describe Verse by Verse, our experiment in augmenting the creative process of writing poetry with an AI. We have created a group of AI poets, styled after various American classic poets, that are able to offer as suggestions generated lines of verse while a user is composing a poem. In this paper, we describe the underlying system to offer these suggestions. This includes a generative model, which is tasked with generating a large corpus of lines of verse offline and which are then stored in an index, and a dual-encoder model that is tasked with recommending the next possible set of verses from our index given the previous line of verse.",
}
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%0 Conference Proceedings
%T Augmenting Poetry Composition with Verse by Verse
%A Uthus, David
%A Voitovich, Maria
%A Mical, R. J.
%Y Loukina, Anastassia
%Y Gangadharaiah, Rashmi
%Y Min, Bonan
%S Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track
%D 2022
%8 July
%I Association for Computational Linguistics
%C Hybrid: Seattle, Washington + Online
%F uthus-etal-2022-augmenting
%X We describe Verse by Verse, our experiment in augmenting the creative process of writing poetry with an AI. We have created a group of AI poets, styled after various American classic poets, that are able to offer as suggestions generated lines of verse while a user is composing a poem. In this paper, we describe the underlying system to offer these suggestions. This includes a generative model, which is tasked with generating a large corpus of lines of verse offline and which are then stored in an index, and a dual-encoder model that is tasked with recommending the next possible set of verses from our index given the previous line of verse.
%R 10.18653/v1/2022.naacl-industry.3
%U https://aclanthology.org/2022.naacl-industry.3
%U https://doi.org/10.18653/v1/2022.naacl-industry.3
%P 18-26
Markdown (Informal)
[Augmenting Poetry Composition with Verse by Verse](https://aclanthology.org/2022.naacl-industry.3) (Uthus et al., NAACL 2022)
ACL
- David Uthus, Maria Voitovich, and R.J. Mical. 2022. Augmenting Poetry Composition with Verse by Verse. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, pages 18–26, Hybrid: Seattle, Washington + Online. Association for Computational Linguistics.