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Construction of rolling machine of steel sections
Křivohlávek, Pavel ; Pavlík, Jan (referee) ; Matějka, Petr (advisor)
The aim of this thesis is to design steel beams bending machine. In the introduction, is characterized by a bending machine and carried out research costs, including factory-produced manufacturers. Followed by a proposal of alternative solutions, evaluating them and selecting the most appropriate conception. The next section is described in detail the proposed model, including stress analysis of loaded parts. The thesis also examined the safety of a forming machine, prepared an analysis of possible defects and their consequences in the design. Finally, it created the design documentation on the proposed machine made pricing and maintenance described rolling machine.
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Internet Voice Search
Belobrad, Michal ; Matějka, Pavel (referee) ; Schwarz, Petr (advisor)
This thesis is concerned with creating applications for touchscreen phones with the operating system Bada. The objective of this application is to allow users to search the web using their voice. We introduce with Samsung Wave for which this application was developed. In addition we look at the results of the recognizer processing, auto-complete, and their combination.
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Code Switching Detection in Speech
Povolný, Filip ; Glembek, Ondřej (referee) ; Matějka, Pavel (advisor)
This master's thesis deals with code-switching detection in speech. The state-of-the-art methods of language diarization are described in the first part of the thesis. The proposed method for implementation is based on acoustic approach to language identification using combination of GMM, i-vector and LDA. New Mandarin-English code-switching database was created for these experiments. Using this system, accuracy of 89,3 % is achieved on this database.
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Speaker Diarization
Tomášek, Pavel ; Karafiát, Martin (referee) ; Matějka, Pavel (advisor)
This work aims at a task of speaker diarization. The goal is to implement a system which is able to decide "who spoke when". Particular components of implementation are described. The main parts are feature extraction, voice activity detection, speaker segmentation and clustering and finally also postprocessing. This work also contains results of implemented system on test data including a description of evaluation. The test data comes from the NIST RT Evaluation 2005 - 2007 and the lowest error rate for this dataset is 18.52% DER. Results are compared with diarization system implemented by Marijn Huijbregts from The Netherlands, who worked on the same data in 2009 and reached 12.91% DER.
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Robust Speaker Verification
Profant, Ján ; Novotný, Ondřej (referee) ; Matějka, Pavel (advisor)
The goal of this paper is to analyze the impact of codec degraded speech on a state-ofthe-art speaker recognition system. Two feature extraction techniques are analyzed - Mel Frequency Cepstral Coefficients (MFCC) and the state-of-the-art system using Bottleneck features together with MFCC. Speaker recognition system is based on i-vector and Probabilistic Linear Discriminant Analysis (PLDA). We compared scenarios where PLDA is trained only on clean data, then system where we added also noise and reverberant data, and at last, codec degraded speech. We evaluated the systems on the matched conditions (data from the same codec are seen with PLDA) and also mismatched conditions (PLDA does not see any data from the tested codec). We experimented also with recently introduced technique for channel adaptation - Within-class Covariance Correction (WCC). We can see clear benefit of adding transcoded data to PLDA or WCC (with approximately same gain) for both tested conditions (matched and mismatched).
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Automation of cam shaft production
Matějka, Petr ; Prokop, Jaroslav (referee) ; Osička, Karel (advisor)
This thesis is intended on modernizing of grinding operations in production cam shafts of injection pump. Existing technology, mainly special-purpose machines, will be replaced by modern CNC grinding machine. Further modernization will take place in the area of measurement, where existing measuring instruments cannot measure profile of cams. There will be used the new measuring machine, which will manage to measure necessary dimensions and tolerances.
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Unsupervised Evaluation of Speaker Recognition System
Odehnal, Ondřej ; Plchot, Oldřich (referee) ; Matějka, Pavel (advisor)
Tato práce je vystavěna nad moderním systémem pro rozpoznávání mluvčího (SID) založeného na x-vektorech. Cílem bakalářské práce je navrhnout a experimentálně vyhodnotit techniky pro evaluaci SID systému za použití audio nahrávek bez anotace tj. bez znalosti mluvčího. Pro tento účel je z každé nahrávky bez anotace vytvořen embedding. Ty se poté používají pro shlukování nahrávek a následné vytvoření pseudo-anotací. Na těchto anotacích se SID systém evaluuje pomocí equal error rate (EER) metriky. Za účelem vytvoření pseudo-anotací byly navrženy tyto shlukovací algoritmy učení bez učitele: K-means, Gaussian mixture models (GMM) a aglomerativní shlukování. Po testování vyšel jakožto nejlepší experimentální postup K-means se Silhouette metrikou, která používá kosinovou podobnost jako míru vzdálenosti. Nejlepší metoda dosáhla 5,72 % EER s referenčním EER = 5,15 %, které bylo spočítané se znalostí anotace na části datasetu SITW dev-core-core. Podobné výsledky byly získány na části datasetu SITW eval-core-core s odhadnutým EER = 5,86 % a referenčním 5,08 %. Rozdíl mezi hodnotami tvoří 0,57 % pro eval-core-core a 0, 78% pro dev-core-core. Další testy na NIST SRE16 a VoxCeleb1 datasetech byly provedeny za účelem ověření správnosti navrženého postupu. Obecně se dá říct, že navržený testovací postup měl chybu přibližně 1 %, což je poměrně dobrý výsledek pro algoritmus učení bez učitele.
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