prikaz prve stranice dokumenta Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki
  Download
PDF 1.85 MB
master's thesis
Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki
Split: University of Split, University of Split, Faculty of science, 2018. urn:nbn:hr:166:855527
Perišić, Frana
University of Split
Faculty of Science
Department of Physics

Institutional repository: Repository of Faculty of Science

Cite this document

Perišić, F. (2018). Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:855527

Perišić, Frana. "Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki." Master's thesis, University of Split, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:166:855527

Perišić, Frana. "Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki." Master's thesis, University of Split, Faculty of Science, 2018. https://urn.nsk.hr/urn:nbn:hr:166:855527

Perišić, F. (2018). 'Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki', Master's thesis, University of Split, Faculty of Science, accessed 11 July 2024, https://urn.nsk.hr/urn:nbn:hr:166:855527

Perišić F. Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki [Master's thesis]. Split: University of Split, Faculty of Science; 2018 [cited 2024 July 11] Available at: https://urn.nsk.hr/urn:nbn:hr:166:855527

F. Perišić, "Primjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki", Master's thesis, University of Split, Faculty of Science, Split, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:166:855527

Metadata
TitlePrimjena metode nezavisnih komponenata u svrhu utvrđivanja govornika iz govornih snimki
Title (english)Application of independent component analysis for identification of speakers from speech recordings
AuthorFrana Perišić
MentorDamir Kovačić (mentor)
Committee memberDamir Kovačić (predsjednik povjerenstva)
Committee memberPetar Stipanović (član povjerenstva)
Committee memberTonko Kovačević (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Physics)
Split
Defense date and country2018-09-14, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Physics
Abstract
U ovom radu je na snimke više govornika primijenjena metoda nezavisnih komponenata (FastICA algoritam u Matlabu) u svrhu izdvajanja izvornih signala. Kada bi se izvorni signali mogli uspješno izdvojiti iz bilo koje mješavine signala to bi mogli primijeniti na niz različitih problema, npr. omogućili bi slušnim aparatima da raspoznaju različite govornike i fokusiraju se na određenog govornika, što je poznato pod nazivom 'cocktail party problem'. Dobiveni rezultati pokazuju da ova metoda funkcionira na snimkama gdje je broj govornika jednak broju mikrofona uz pretpostavku da su izlazne vrijednosti mikrofona linearne mješavine nezavisnih komponenti. Ljudski govor je sam po sebi jako kompleksan, a to posebno dolazi do izražaja kad istovremeno govori više govornika. Otkrivanje mehanizma selektivne pozornosti u mozgu je ključ za rješavanje 'cocktail party problem'.
Abstract (english)
In this paper was applied independent component analysis (FastICA algorithm in Matlab) on the records of more speakers for the purpose of extracting the original signals. If the source signals could be successfully extracted from any signal mixture they could apply to a variety of different problems, for example, allow hearing aids to discern different speakers and focus on a particular speaker, known as the 'cocktail party problem'. The results obtained show that this method works on experimental recordings where the number of speakers is equal to the number of microphones assuming that the output values of the microphone are linear mixtures of independent components. Human speech is very complex by itself, and this is particularly pronounced when multiple speakers speak simultaneously. Detecting a selective attention mechanism in the brain is the key to solving the 'cocktail party problem'.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:855527
Study programmeTitle: Physics; specializations in: major in teaching, major in Astrophysics, major in Biophysics, major in Enviromental physics, major in Computational physics
Course: major in Biophysics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra fizike (magistar/magistra fizike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Embargo expiration date: 2019-03-14
Terms of useLicence In copyright icon
Created on2018-12-07 16:10:48