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master's thesis
Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:747704
Banić, Luka
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Banić, L. (2024). Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:747704

Banić, Luka. "Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:747704

Banić, Luka. "Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:747704

Banić, L. (2024). 'Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:747704

Banić L. Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 November 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:747704

L. Banić, "Raspoznavanje emocija u govoru korištenjem paradigme dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:747704

Metadata
TitleRaspoznavanje emocija u govoru korištenjem paradigme dubokog učenja
Title (english)Recognizing emotions in speech using deep learning paradigm
AuthorLuka Banić
MentorAnamari Nakić (mentor)
Committee memberAnamari Nakić (predsjednik povjerenstva)
Committee memberJosipa Pina Milišić (član povjerenstva)
Committee memberDomagoj Kovačević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-03, Croatia
Abstract
U ovome je radu prikazan razvoj modela strojnoga učenja za raspoznavanje emocija u govoru. Model dubokoga učenja razvijen na temelju paradigme nezavisnosti o govorniku, vrši zadatak višeklasne klasifikacije šest emocija iz CREMA-D baze audiozapisa. Konačni model kombinira arhitekture konvolucijskih mreža i transformerskoga enkodera. Dobiveni rezultati pokazuju veću točnost od procjena ljudi u istim uvjetima raspoznavanja. Analiziraju se potencijalne karakteristike ljudske emocionalne ekspresije koje su mogući uzročnik različite izvedbe modela ovisno o emociji te mogućnost i prepreke konstrukcije baze emocionalnih audiozapisa drugačije strukture. Konačno, razvijena je web-aplikacija u sklopu koje je implementiran model za jednostavnu primjenu na proizvoljnome audiozapisu.
Abstract (english)
In this paper, the development of a machine learning model for speech emotion recognition is presented. The deep learning model, developed based on the speaker-independent paradigm, performs the task of multi-class classification of six emotions from the CREMA-D audio database. The final model combines architectures of convolutional networks and transformer encoders. The obtained results demonstrate greater accuracy than human benchmarks under the same recognition conditions. Potential characteristics of human emotional expression, which may cause varying model performance depending on the emotion, are explored, as well as the possibilities and obstacles in constructing a database of emotional audio recordings with a different structure. Finally, a web application has been developed within which the model is implemented for straightforward application to any audio recording.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:747704
Study programmeTitle: Computing
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
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Created on2024-10-12 20:02:01