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Voice Activity Detection
Břenek, Roman ; Grézl, František (referee) ; Matějka, Pavel (advisor)
This thesis describes techniques for voice activity detection in audio recordings. It is necessary to correctly classify all non-speech segments and recognize speech with noisy background. The whole process of voice activity detection (VAD) is described in this thesis, i.e. digitizing audio signal, feature extraction, training of the system, post-processing and final evaluation. There are three different systems compared within the thesis . The first one is based on phoneme recognition using neural network, the other two are variations of Gaussian Mixture Models (GMM). Each system was tested on three data sets - Tactical Speaker Identification Speech Corpus (TSID), Ham Radio (HR) and Rich Transcription Evaluation (RT05-RT07). The best results of each system are compared with the results of the third side.
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Simple Character Recognition
Hamrský, Jan ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
This work deals with the process of text location and recognition in an image document. It discusses the matter of feature extraction and its usage in machine learning. Portion of this work is devoted to design and implementation of application for simple character recognition of machine printed text.
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Software for Biometric Recognition of a Human Eye Iris
Maruniak, Lukáš ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
In my thesis, I focus on the task of recognizing human iris from an image.In the beginning, the work deals with a question of biometrics, its importance and basic concepts, which are necessary for use in following text. Subsequently process of human Iris detection is described together with theory of evolution algorithms. In the implementation part, is described the design of implemented solution, which uses evolution algorithms, where is emphasis on correct pupil and iris boundary detection.
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ECG signal quality annotation
Waloszek, Vojtěch ; Smíšek, Radovan (referee) ; Vítek, Martin (advisor)
This thesis gives basic information summary about electrophysiology of heart and electrocardiography and overview of several signal quality assessment methods. It also presents a new method for evaluating ECG quality, shows how signal quality indices are extracted and how the quality annotation is performed. It also gives test results of how the signal quality indices reflect the presence of corresponding noise and whether the quality annotation is correct.
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Multicameras Biometric Gateway to Identify People
Kosík, Dominik ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This thesis is about creating biometric gate to identify people. The Identification is achieved with 5 RGB cameras and one thermal camera. Thermal camera is used for detection of person. Then, from images acquired from RGB cameras, is created 3D model of photographed person. This model is then used for the identification. However due to inaccuracies in created model, identification isn't precise enough. Because of that, it's necessary to modify used algorithms processing 3D model, so better precision is achieved.
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Automatic detection of stress using biological signals
Votýpka, Tomáš ; Kozumplík, Jiří (referee) ; Smíšek, Radovan (advisor)
Bachelor's thesis is focused on stress detection. This thesis defines the concept of stress, analyzes the appropriate biological signals for stress detection, presents databases of biological signals, that were used for stress detection and mentions methods of automatic stress detection. Then, a stress detection program was implemented in the MATLAB software environment. A freely available database of non-EEG signals was used to implement the program. Models classifying stress were created using 4 machine learning methods for binary classification and 3 machine learning methods for classifying 4 psychical states. Efficiency of the classification was summarized in the conclusion of this thesis.
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Multimedia Document Type Diff
Lang, Jozef ; Hlosta, Martin (referee) ; Chmelař, Petr (advisor)
Development of Internet and its massive spread resulted in increased volume of multimedia data. The increase in the amount of multimedia data raises the need for efficient similarity detection between multimedia files for the purpose of preventing and detecting violations of copyright licenses or for detection of similar or duplicate files. This thesis discusses the current options in the field of the content-based image and video comparison and focuses on the feature extraction techniques, distance metrics, design and implementation of the mediaDiff application module for the content-based comparison of video files.
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Music Style Recognizer from MP3
Deutscher, Michael ; Szőke, Igor (referee) ; Grézl, František (advisor)
This document describes the concept of music style recognition. It gives a quick reference to the digitalization of music data and storing music data in computers. It also mentions features used for music style recognition and their extraction. The main part of this document compares the successfulness of music genre recognition using features extracted directly from audio data in mp3 format and features extracted by usual analysis.
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Keyword Spotting Implementation to Mobil Phone (Symbian 60)
Cipr, Tomáš ; Schwarz, Petr (referee) ; Szőke, Igor (advisor)
Keyword spotting is one of the many applications of automatic speech recognition. Its purpose is determining spots in given utterance in which some of the specified words were spoken. Keyword spotting has a great potential to enhance performance of new applications as well as the existing ones. An example could be a mobile phone voice control. Due to OS Symbian's coming to the market it is even possible for end user to implement a keyword spotting for a mobile phone on his or her own. The thesis describes theoretical prerequisites for keyword spotting and its implementation. Firstly the OS Symbian is presented with respect to the given task. Secondly each step of keyword spotting process is described. Finally the object design of keyword spotter is presented followed by implementation description. The thesis concludes with results review and notes on possible improvements.
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Trully Smart Smart Socket
Valušek, Ondřej ; Zemčík, Pavel (referee) ; Materna, Zdeněk (advisor)
There is a large selection of so called smart sockets available on the market today. The possibilities of these sockets are sadly very limited. Typically, they can measure power consumption, be turned off and on remotely by mobile application and timer. This thesis deals with this problem by showing how a smart relay can be used to create a truly smart smart socket that can classify currently connected appliances using just short time window for up to three devices combined. The power consumption is measured using Shelly 1PM together for three plugs. Using time series feature extraction, unknown device detection with SVM and neural network classification, the accuracy was over 99%. on a dataset containing combinations of smart TV, lamp and a laptop consumption. Information about currently connected devices is displayed on a webpage and written to a database to be viewed later. The information about connecting and disconnecting a device can be further sent to a system for smart home management.
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