dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Vreeswijk, G.A.W. | |
dc.contributor.author | Mooij, A.J. de | |
dc.date.accessioned | 2016-04-21T17:00:28Z | |
dc.date.available | 2016-04-21T17:00:28Z | |
dc.date.issued | 2016 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/22208 | |
dc.description.abstract | In this thesis, we discuss various poetry generators. We present our own text synthesis and natural language generation algorithm that can be used with various machine learning technologies, as well as a setup for the final machine learning enabled poetry generator, which we call EvoPoem. The algorithm is able to produce short, grammatically correct sentences, and create a visual spacing that suggests rhythm. This algorithm uses a grammar, a lexicon and a feature and unification algorithm enriched with constraint satisfaction, to parse a string of bits deterministically into a potential poem. | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 633769 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.title | EvoPoem: Context Free Grammars for Automated Poetry Generation | |
dc.type.content | Bachelor Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Evolutionary Art; Machine Learning; Genetic Algorithms; Poetry Generation | |
dc.subject.courseuu | Kunstmatige Intelligentie | |