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Web-Based Demonstration of Linear Filtering
Novotný, Ondřej ; Bařina, David (referee) ; Černocký, Jan (advisor)
The aim of this work is to create a demonstration application of discrete linear filtering. The introductory section summarizes the theory of digital filtering and filter design. The following chapter describes the existing applets. Subsequently, the concept of the demonstration and its implementation are described. The final part contains tutorial examples of using the demonstration and summary of users' reactions.
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Melody Harmonization
Vlasák, Jaroslav ; Černocký, Jan (referee) ; Fapšo, Michal (advisor)
This bachaleor's thesis is focused on an automatic harmonization of melody. The implemented system is using a machine learning approach and learning the harmony principles from the database of MIDI files. The input of the system could be monophony songs in MIDI or ABC format. The output of the system are polyphony songs in MIDI format harmonized in the style of protestant chorale.
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Sound Creation Using VST
Švec, Michal ; Schimmel, Jiří (referee) ; Černocký, Jan (advisor)
This diploma thesis deals with digital sound synthesis. The main task was to design and implement new sound synthesizer. Created tool uses different approaches to the sound synthesis, so it can be described as a hybrid. Instrument design was inspired by existing audio synthesizers. For implementation, C++ language and VST technology from Steinberg are used. As an extension, a module, that can process voice or text input and then build a MIDI file with melody (which can be interpreted with using any synthesizer) was designed and implemented. For this module, Python language is used. For the synthesizer, a simple graphical user interface was created.
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Chord recognition
Soudek, Ondřej ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
The goal of this bachelor thesis is to create an application, that will perform a real-time analysis of a signal from electric or acoustic guitar and will recognize a chord or tone, played by user. This document contains basics of music theory and the solution of the problem, as well as the results of testing.
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Echo-Based Distance Measurement on Mobile Phone
Richter, Jiří ; Maršík, Lukáš (referee) ; Černocký, Jan (advisor)
Cílem této práce je vytvoření aplikace pro mobilní zařízení na měření vzdálenosti pomocí ozvěny. Zaměřuje se na testování komponent zařízení a výběr signálu s vhodnými parametry pro měření. První částí práce je vyhodnocení schopnosti zařízení přehrávat a nahrávat zvuk, výsledkem je určení frekvence a síly zvuku, se kterým je zařízení schopno pracovat. Práce dále popisuje algoritmus pro měření vzdálenosti založeny na vzájemné korelaci vyslaného a přijatého signálu. Další částí je popis implementace výše zmíněného algoritmu v aplikaci pro operačním systému Android s řešením komunikace a synchronizace mezi jednotlivými součástmi. Implementace navrženého algoritmu v aplikace je v závěru práce otestována. Na základě zjištěných údajů je možné měření vzdálenosti na mobilním zařízení od půl metru do přibližně tří metrů, s ohledem na okolní hluk, s přesností na desetinu metru.
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AutoRapper - Automatic Alignment of Speech with a Rhythm
Poliak, Sebastián ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
Tato práce popisuje návrh a implementaci aplikace, která automaticky převádí vstupní řeč na rap. Tento proces je založen na zarovnání řeči s rytmem, které je dosaženo pomocí rozpoznávání fonémù, slabikování a časové modifikáce řeči. Další funkce, jako je hudební podklad a vokální efekt jsou přidány za účelem přiblížení se ke skutečnému rapu. Výsledná aplikace je dostupná jako webová služba pro uživatele.
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Automatic Link Detection in Parts of Audiovisual Documents
Sychra, Marek ; Černocký, Jan (referee) ; Szőke, Igor (advisor)
This paper deals with topic detection. Specifically link detection - finding similarities amongst a group of short documents according to their topic and story segmentation - finding borders between two topically different parts in a large document. The main motivation for research was practical application with the use of presentation materials from lectures at FIT (linking parts of different lectures and courses). The solution of link detection is achieved by text and word analysis, which includes learning the meaning and importance of each word. Story segmentation uses this while searching for the boundaries. Both parts of the problem (link detection, story segmentation) gave great results while testing with a standard dataset (world news reports). During evaluation of lecture processing the success rate was lower, but still good.
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Comparison of Accuracy of Siri, Cortana and Google
Procingerová, Lucie ; Černocký, Jan (referee) ; Szőke, Igor (advisor)
The aim of this thesis is to compare the accuracy of translation of spoken word into text using several services. Primary it is about applications from Apple Inc., Microsoft Corporation and Google Inc., but there is also included several others, mostly available on-line. This document contains a descriptionn of the problem, analyzes the progress for each service. Subsequently, the test results are analyzed and compared with the reference outputs. In conclusion, there is a discussion of these experiments.
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Prediction of Prices in Stock Exchange Trading
Mikulenčák, Roman ; Szőke, Igor (referee) ; Černocký, Jan (advisor)
The work deals with an automatic trading system and adaptive training. Is used both technical and automatic fundamental analyses, therefore as inputs to the neural network is used historical data exchanges and text data from reports. It explains the basics of trading, technical analysis and technical terms. The work deals with technical and fundamental analysis. It contains a description of algorithmic nature, program implementation and experiment with developed trading system. The selected strategy is compared to other approaches.
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Recognition of Home Appliances Based on Their Power Consumption Characteristics
Vaňková, Klára ; Černocký, Jan (referee) ; Schwarz, Petr (advisor)
The goal of this master's thesis is to design and implement a system for recognition of home appliances based on their power consumption characteristics. This system should identify the individual home appliances from measurements of the total household consumption. The acquired data could be used for statistics of usage of a particular appliance and subsequent detection of errors or non-standard behavior of the measured device. An important part of my work is a design and hardware implementation of a unit for measuring and a system for processing the measured signal. The first version of my project uses pulse output of an electrometer to measure the energy. This method does not provide a sufficient sample rate but it's a quick way to obtain data for processing and analysis. The second version monitors the power consumption with a multi-purpose AC converter which measures active and reactive power with the desired sample rate. The data is then processed and recognized by two classifiers - HMM and KNN.
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