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The phoneme set influence for Lithuanian speech commands recognition accuracy

dc.rights.licenseVisos teisės saugomos / All rights reserveden_US
dc.contributor.authorGreibus, Mindaugas
dc.contributor.authorRingelienė, Živilė
dc.contributor.authorTelksnys, Laimutis
dc.date.accessioned2025-12-04T09:58:43Z
dc.date.available2025-12-04T09:58:43Z
dc.date.issued2017
dc.identifier.isbn9781538639993en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/159481
dc.description.abstractThe phoneme set influence for Lithuanian speech commands recognition accuracy is investigated. Four phoneme sets are discussed. LIEPA speech corpus for training of Acoustic Model is used. The phonetic representation of corpus transcriptions is generated by grapheme-to-phoneme transformation rules. Rule based transformations for Lithuanian language is proposed. Recognition engine with CMU Pocketsphinx decoder is used. Experimental investigation with fixed size test corpus demonstrates that 36 (FZ1.3) phonemes set shows the bests result.en_US
dc.format.extent4 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/159383en_US
dc.source.urihttps://ieeexplore.ieee.org/document/7950321en_US
dc.subjectspeech recognitionen_US
dc.subjectautomatic transcriptionen_US
dc.subjectacoustic model trainingen_US
dc.subjectgrapheme to phoneme transcriptionen_US
dc.titleThe phoneme set influence for Lithuanian speech commands recognition accuracyen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.issued2017-06-19
dcterms.references21en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionVilnius Universityen_US
dcterms.sourcetitle2017 Open Conference of Electrical, Electronic and Information Sciences (eStream), April 27, 2017, Vilnius, Lithuaniaen_US
dc.identifier.eisbn9781538639986en_US
dc.publisher.nameIEEEen_US
dc.publisher.countryUnited States of Americaen_US
dc.publisher.cityNew Yorken_US
dc.identifier.doihttps://doi.org/10.1109/eStream.2017.7950321en_US


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