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Speaker Segmentation using statistical methods of classification
Adamský, Aleš ; Přinosil, Jiří (oponent) ; Smékal, Zdeněk (vedoucí práce)
The thesis discusses in detail some concepts of speech and prosody that can contribute to build a speech corpus for the speaker segmentation purpose. Moreover, the Elan multimedia annotator used for labeling is described. The theoretical part highlights some frequently used speech features such as MFCC, PLP and LPC and deals with currently most popular speech segmentation methods. Some classification algorithms are also mentioned. The practical part describes implementation of Bayesian information criterium algorithm in system for automatic speaker segmentation. For classification of speaker change point in speech, were used different speech features. The results of tests were evaluated by the graphic method of receiver operating characteristic (ROC) and his quantitative indices. As the best speech features for this system were provided MFCC and HFCC.
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Predicting Czech Economic Activity Using Toll Data
Učňová, Jana ; Kocourek, David (vedoucí práce) ; Šestořád, Tomáš (oponent)
Mnoho analytiků se shoduje v tom, že doprava je zce spojena s ekonomickou aktivitou. Nicmně, data obsahujc informace o dopravě dlouhou dobu nebyla součst jejich vzkumů. Zaveden elektronickch systmů vběru mtnho vedlo v nedvn době k novmu zdroji dat, kter obsahuj informace o kamionov dopravě. Jsou tedy užitečnm zdrojem infromac, kter může bt použit k předpovědi ekonomick aktivity. Clem tto prce je zkoumn schopnosti seznně očištěnch dat z mtnch bran předpovdat ekonomickou aktivitu Česk republiky. Ekonomick aktivita je zastoupena čtyřmi proměnnmi - relnm HDP, nominlnm HDP, indexem průmyslov produkce a objemem zahraničnho obchodu. Sedm modelů - pět dynamickch modelů, ARIMA model a regrese s ARIMA chybou - jsou sestraveny pro každou zvislou proměnnou. Tyto modely jsou pot srovnny pomoc Akaikeho a Bayesova informačnch kritri a pro každou zvislou proměnnou je vybrn ten nejvhodnějš model. Jak reln HDP, tak i index průmyslov produkce lze předpovědět pomoc mtnch dat a počet projetch kilometrů i vybranho mta se zd bt dobrm prediktorem ekonomick aktivity. Zejmna, vybran mto může bt přnosnějš, jelikož lze pomoc něj předvdat ekonomickou aktivitu dokonce i v nsledujcm kvartlu. 1
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Risk factor modeling of Hedge Funds' strategies
Radosavčević, Aleksa ; Princ, Michael (vedoucí práce) ; Šopov, Boril (oponent)
This thesis aims to identify main driving market risk factors of different strategies implemented by hedge funds by looking at correlation coefficients, implementing Principal Component Analysis and analyzing "loadings" for first three principal components, which explain the largest portion of the variation of hedge funds' returns. In the next step, a stepwise regression through iteration process includes and excludes market risk factors for each strategy, searching for the combination of risk factors which will offer a model with the best "fit", based on The Akaike Information Criterion - AIC and Bayesian Information Criterion - BIC. Lastly, to avoid counterfeit results and overcome model uncertainty issues a Bayesian Model Average - BMA approach was taken. Key words: Hedge Funds, hedge funds' strategies, market risk, principal component analysis, stepwise regression, Akaike Information Criterion, Bayesian Information Criterion, Bayesian Model Averaging Author's e-mail: aleksaradosavcevic@gmail.com Supervisor's e-mail: mp.princ@seznam.cz
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Speaker Segmentation using statistical methods of classification
Adamský, Aleš ; Přinosil, Jiří (oponent) ; Smékal, Zdeněk (vedoucí práce)
The thesis discusses in detail some concepts of speech and prosody that can contribute to build a speech corpus for the speaker segmentation purpose. Moreover, the Elan multimedia annotator used for labeling is described. The theoretical part highlights some frequently used speech features such as MFCC, PLP and LPC and deals with currently most popular speech segmentation methods. Some classification algorithms are also mentioned. The practical part describes implementation of Bayesian information criterium algorithm in system for automatic speaker segmentation. For classification of speaker change point in speech, were used different speech features. The results of tests were evaluated by the graphic method of receiver operating characteristic (ROC) and his quantitative indices. As the best speech features for this system were provided MFCC and HFCC.
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