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master's thesis
Sinteza govora iz teksta upotrebom dubokog učenja
2020. urn:nbn:hr:200:883519
Džijan, Matej
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

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Džijan, M. (2020). Sinteza govora iz teksta upotrebom dubokog učenja (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:883519

Džijan, Matej. "Sinteza govora iz teksta upotrebom dubokog učenja." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2020. https://urn.nsk.hr/urn:nbn:hr:200:883519

Džijan, Matej. "Sinteza govora iz teksta upotrebom dubokog učenja." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2020. https://urn.nsk.hr/urn:nbn:hr:200:883519

Džijan, M. (2020). 'Sinteza govora iz teksta upotrebom dubokog učenja', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 30 December 2024, https://urn.nsk.hr/urn:nbn:hr:200:883519

Džijan M. Sinteza govora iz teksta upotrebom dubokog učenja [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2020 [cited 2024 December 30] Available at: https://urn.nsk.hr/urn:nbn:hr:200:883519

M. Džijan, "Sinteza govora iz teksta upotrebom dubokog učenja", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:200:883519

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Metadata
TitleSinteza govora iz teksta upotrebom dubokog učenja
Title (english)Text to speech using deep learning
AuthorMatej Džijan
MentorRatko Grbić (mentor)
Committee memberRatko Grbić (predsjednik povjerenstva)
Committee memberEmmanuel Karlo Nyarko (član povjerenstva)
Committee memberPetra Đurović (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Computer Engineering and Automation)
(Chair of Automation and Robotics)
Osijek
Defense date and country2020-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
Ovaj diplomski rad se bavi problematikom sinteze govora iz teksta. Cilj rada bio je realizirati model za sintezu govora iz teksta za hrvatski jezik. Za početak je dana osnovna terminologija ovog područja. Nakon toga su uspoređena neka od postojećih rješenja za problem sinteze govora iz teksta. Zadatak ovog diplomskog rada riješen je korištenjem modela Tacotron 2, koji je detaljno objašnjen. Za potrebe učenja, prvo je izrađen podatkovni skup sastavljen od pročitanih rečenica na hrvatskom jeziku s pripadajućim transkriptom. Nakon izrade podatkovnog skupa, model je prilagođen za hrvatski jezik. Model je treniran na predtreniranom modelu za engleski jezik što je uvelike ubrzalo i olakšalo treniranje. Nakon treniranja, odabran je konačni model koji je dalje evaluiran. Model je evaluiran korištenjem anketa u kojima su ispitanici ocjenjivali sintetizator na testnim rečenicama, uspoređivali ih s izgovorenim rečenicama i ocjenjivali sintetizator na rečenicama podijeljenim u kategorije. Također je provedena i analiza pogrešaka u sintetiziranim rečenicama.
Abstract (english)
This thesis deals with the issue of speech synthesis from text. The aim of the paper was to realize a text-to-speech model for the Croatian language. To begin with, the basic terminology of the area was given. After that, some of the existing solutions for text-to-speech were compared. The task of this thesis was solved using the Tacotron 2 model, which is explained in detail. For training purposes, a data set consisting of read sentences in Croatian with the accompanying transcript was first created. After creating the data set, the model was adapted for the Croatian language. The model was trained on a pre-trained model for the English language which greatly accelerated and facilitated the training. After training, the final checkpoint was selected which was then used for evaluation. The model was evaluated using surveys in which subjects rated the synthesizer on test sentences, compared them to spoken sentences, and rated the synthesizer on sentences divided into categories. Error analysis of the synthesized sentences was also performed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:883519
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-11-19 10:49:19