Heuristic Hyper-minimization of Finite State Lexicons

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dc.contributor.author Drobac, Senka
dc.contributor.author Linden, Krister
dc.contributor.author Pirinen, Tommi
dc.contributor.author Silfverberg, Miikka
dc.date.accessioned 2014-10-18T21:12:32Z
dc.date.available 2014-10-18T21:12:32Z
dc.date.issued 2014-05-26
dc.identifier.citation Drobac , S , Linden , K , Pirinen , T & Silfverberg , M 2014 , Heuristic Hyper-minimization of Finite State Lexicons . in Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14) . vol. 9 , #784 , European Language Resources Association (ELRA) , Reykjavik, Iceland , Language Resource and Evaluation Conference , Reykjavik , Iceland , 26/05/2014 .
dc.identifier.citation conference
dc.identifier.other PURE: 42017152
dc.identifier.other PURE UUID: b31cb290-1e03-45bb-bd0b-8456e411bde6
dc.identifier.other Scopus: 84995346955
dc.identifier.other ORCID: /0000-0003-2337-303X/work/29934323
dc.identifier.other ORCID: /0000-0002-7645-3079/work/29577413
dc.identifier.uri http://hdl.handle.net/10138/136266
dc.description Proceeding volume: 9
dc.description.abstract Flag diacritics, which are special multi-character symbols executed at runtime, enable optimising finite-state networks by combining identical sub-graphs of its transition graph. Traditionally, the feature has required linguists to devise the optimisations to the graph by hand alongside the morphological description. In this paper, we present a novel method for discovering flag positions in morphological lexicons automatically, based on the morpheme structure implicit in the language description. With this approach, we have gained significant decrease in the size of finite-state networks while maintaining reasonable application speed. The algorithm can be applied to any language description, where the biggest achievements are expected in large and complex morphologies. The most noticeable reduction in size we got with a morphological transducer for Greenlandic, whose original size is on average about 15 times larger than other morphologies. With the presented hyper-minimization method, the transducer is reduced to 10,1% of the original size, with lookup speed decreased only by 9,5%. en
dc.format.extent 6
dc.language.iso eng
dc.publisher European Language Resources Association (ELRA)
dc.relation.ispartof Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
dc.relation.isversionof 978-2-9517408-8-4
dc.relation.isversionof 978-2-9517408-8-4
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 113 Computer and information sciences
dc.subject finite-state transducers
dc.subject hyper-minimization
dc.subject 6121 Languages
dc.subject lexicon
dc.title Heuristic Hyper-minimization of Finite State Lexicons en
dc.type Conference contribution
dc.contributor.organization Department of Modern Languages 2010-2017
dc.contributor.organization Krister Linden / Research Group
dc.contributor.organization Phonetics and Speech Synthesis
dc.description.reviewstatus Peer reviewed
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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