Can Human Assistance Improve a Computational Poet
Inhaltsverzeichnis
Reference
Carolyn E. Lamb, Daniel G. Brown and Charles L.A. Clarke: Can Human Assistance Improve a Computational Poet? In: Bridges 2015. Pages 37–44
DOI
Abstract
Good computational poetry requires sufficiently interesting poetic phrases to be generated or chosen. Different metrics for determining what makes a sufficiently interesting phrase have rarely been directly compared. We directly compare of a number of metrics—topicality, sentiment, and concrete imagery—by collecting human judgments on each metric for the same data set of human-generated phrases, then having humans judge computationally generated poems chosen to include high-scoring phrases against each other. We find through a quantitative analysis that the output of at least some of these metrics is perceived as better than output using none of these metrics.
Extended Abstract
Bibtex
@inproceedings{bridges2015:37,
author = {Carolyn E. Lamb, Daniel G. Brown and Charles L.A. Clarke},
title = {Can Human Assistance Improve a Computational Poet?},
pages = {37--44},
booktitle = {Proceedings of Bridges 2015: Mathematics, Music, Art, Architecture, Culture},
year = {2015},
editor = {Kelly Delp, Craig S. Kaplan, Douglas McKenna and Reza Sarhangi},
isbn = {978-1-938664-15-1},
issn = {1099-6702},
publisher = {Tessellations Publishing},
address = {Phoenix, Arizona},
note = {Available online at \url{http://archive.bridgesmathart.org/2015/bridges2015-37.html }},
url = {http://de.evo-art.org/index.php?title=Can_Human_Assistance_Improve_a_Computational_Poet },
}
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Links
Full Text
http://archive.bridgesmathart.org/2015/bridges2015-37.pdf
