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AfriKI: machine-in-the-Loop Afrikaans poetry generation

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dc.contributor.coauthorBaş, Anıl
dc.contributor.departmentDepartment of Comparative Literature
dc.contributor.kuauthorvan Heerden, Imke
dc.contributor.kuprofileOther
dc.contributor.otherDepartment of Comparative Literature
dc.contributor.schoolcollegeinstituteCollege of Social Sciences and Humanities
dc.contributor.yokid318142
dc.date.accessioned2024-11-10T00:05:33Z
dc.date.issued2021
dc.description.abstractThis paper proposes a generative language model called AfriKI. Our approach is based on an LSTM architecture trained on a small corpus of contemporary fiction. With the aim of promoting human creativity, we use the model as an authoring tool to explore machine-in-the-loop Afrikaans poetry generation. To our knowledge, this is the first study to attempt creative text generation in Afrikaans.
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.identifier.doiN/A
dc.identifier.isbn9781-9540-8517-6
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85123319896&partnerID=40&md5=117003bed6b89b14fd548a348917e047
dc.identifier.scopus2-s2.0-85123319896
dc.identifier.urihttps://hdl.handle.net/20.500.14288/16466
dc.keywordsComputational linguistics
dc.keywordsNatural language processing systems
dc.keywordsAuthoring tool
dc.keywordsCreatives
dc.keywordsHuman creativity
dc.keywordsLanguage model
dc.keywordsText generations
dc.keywordsLong short-term memory
dc.languageEnglish
dc.publisherAssociation for Computational Linguistics (ACL)
dc.sourceBridging Human-Computer Interaction and Natural Language Processing, HCINLP 2021 - Proceedings of the 1st Workshop
dc.subjectComputer Science
dc.subjectArtificial intelligence
dc.titleAfriKI: machine-in-the-Loop Afrikaans poetry generation
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authorid0000-0002-4224-8800
local.contributor.kuauthorvan Heerden, Imke
relation.isOrgUnitOfPublication4d7bb696-a523-4c96-8832-64baef1b8b21
relation.isOrgUnitOfPublication.latestForDiscovery4d7bb696-a523-4c96-8832-64baef1b8b21

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