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Adaptace rozpoznávače řeči na datech bez přepisu / Unsupervised Adaptation of Speech Recognizer

The goal of this thesis is to design and test techniques for unsupervised adaptation of speech recognizers on some audio data without any textual transcripts. A training set is prepared at first, and a baseline speech recognition system is trained. This sistem is used to transcribe some unseen data. We will experiment with an adaptation data selection process based on some speech transcript quality measurement. The system is re-trained on this new set than, and the accuracy is evaluated. Then we experiment with the amount of adaptation data.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:234944
Date January 2015
CreatorsŠvec, Ján
ContributorsKarafiát, Martin, Schwarz, Petr
PublisherVysoké učení technické v Brně. Fakulta informačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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