{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-speare-a-joint-neural-model-of-poetic","title":"Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhyme","arxiv_id":"1807.03491","date":"2018-07-10","proceeding":"ACL 2018 7","authors":["Jey Han Lau","Trevor Cohn","Timothy Baldwin","Julian Brooke","Adam Hammond"],"abstract":"In this paper, we propose a joint architecture that captures language, rhyme\nand meter for sonnet modelling. We assess the quality of generated poems using\ncrowd and expert judgements. The stress and rhyme models perform very well, as\ngenerated poems are largely indistinguishable from human-written poems. Expert\nevaluation, however, reveals that a vanilla language model captures meter\nimplicitly, and that machine-generated poems still underperform in terms of\nreadability and emotion. Our research shows the importance expert evaluation\nfor poetry generation, and that future research should look beyond rhyme/meter\nand focus on poetic language.","url_abs":"http://arxiv.org/abs/1807.03491v1","url_pdf":"http://arxiv.org/pdf/1807.03491v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-speare-a-joint-neural-model-of-poetic","repo_url":"https://github.com/jhlau/deepspeare","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1807.03491","atlas_url":"https://app.syntology.ai/?focus=1807.03491","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}