<p>U okviru ove disertacije razvijeno je više različitih modela trajanja glasova u srpskom jeziku primenom odgovarajućih metoda automatskog učenja. Izvršena je objektivna evaluacija razvijenih modela i njihovo međusobno poređenje na osnovu kvantitativnih pokazatelja kao što su RMSE(engl. root-mean-squared error), MAE (engl. mean absolute error) i CC (engl. correlation coefficient). Takođe je izvršeno poređenje modela za srpski jezik sa performansama modela razvijenih za druge jezike, pri čemu je uočeno da su performanse modela razvijenih u ovoj disertaciji uporedljive ili čak prevazilaze performanse modela koji su razvijeni za druge jezike.</p> / <p>In this dissertation several different phone duration models of the Serbain<br />language using appropriate machine learning algorithms were developed.<br />The objective evaluation of the models obtained and their mutual comparison<br />based on quantitative measures such as RMSE (root-mean-squared error),<br />MAE (mean absolute error) and CC (correlation coefficient) were performed.<br />The comparison of the models developed for the Serbian language with the<br />performances of the models developed for other languages is also carried<br />out. It was observed that the performances of the models developed in this<br />dissertation are comparable or even outperform the performances of the<br />models that have been developed for other languages.</p>
Identifer | oai:union.ndltd.org:uns.ac.rs/oai:CRISUNS:(BISIS)85851 |
Date | 10 July 2014 |
Creators | Sovilj-Nikić Sandra |
Contributors | Delić Vlado, Hadžić Olga, Bajić Dragana, Jovičić Slobodan, Marković Maja |
Publisher | Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, University of Novi Sad, Faculty of Technical Sciences at Novi Sad |
Source Sets | University of Novi Sad |
Language | Serbian |
Detected Language | Unknown |
Type | PhD thesis |
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