Stochastic semantic analysis: technical report no. DCSE/TR-2009-04

dc.contributor.authorHabernal, Ivan
dc.date.accessioned2016-06-22T09:57:18Z
dc.date.available2016-06-22T09:57:18Z
dc.date.issued2009
dc.description.abstract-translatedIn human-computer dialogue systems, the task of Spoken Language Understanding (SLU) system is to process the input acoustic utterance and transform it into a semantic representation. The goal of semantic analysis is to represent what the subject intended to say. This thesis presented overview of the current state-of-the-art methods for statistical semantic analysis. In comparison to the expert based systems, the main advantage of stochastic approaches is the ability to train the model from data. Furthermore, systems based on statistical models can be easily ported to other domains. However, the amount of the annotation effort must be also taken into account when developing the stochastic semantic analysis system. In this thesis, fundamental stochastic models along with the training and evaluation of these models are described.en
dc.format42 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://www.kiv.zcu.cz/publications/
dc.identifier.urihttp://hdl.handle.net/11025/21575
dc.language.isoenen
dc.publisherUniversity of West Bohemia in Pilsenen
dc.rights© University of West Bohemia in Pilsenen
dc.rights.accessopenAccessen
dc.subjectdialogový systémcs
dc.subjectporozumění mluvené řečics
dc.subjectstochastické modelycs
dc.subject.translateddialogue systemen
dc.subject.translatedspoken language understandingen
dc.subject.translatedstochastic modelsen
dc.titleStochastic semantic analysis: technical report no. DCSE/TR-2009-04en
dc.typezprávacs
dc.typereporten
dc.type.versionpublishedVersionen

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