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Recognising the Genre of Popular Songs
Čižmár, Filip ; Janoušek, Vladimír (referee) ; Zbořil, František (advisor)
The aim of this thesis is to get acquainted with the principles of working with sound in the Python programming language and with the issue of convolutional neural networks in order to create a web application capable of recognizing the genre of an uploaded song. The thesis describes the principles of machine learning with a focus on convolutional neural networks. A considerable part of this thesis is devoted to the research of available datasets created for the purpose of music information retrieval. Next, the process of preparation of the selected dataset and transformation of audio information into spectrograms for the learning of convolutional neural networks is described. Two models capable of recognizing the genre of music were created as a part of the thesis. First, for general, more popular genres and the second focuses on subgenres of electronic music. The result is a web application that, after a song is uploaded, displays the probabilities of classification into individual genres.
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Recognising the Genre of Popular Songs
Čižmár, Filip ; Janoušek, Vladimír (referee) ; Zbořil, František (advisor)
The aim of this thesis is to get acquainted with the principles of working with sound in the Python programming language and with the issue of convolutional neural networks in order to create a web application capable of recognizing the genre of an uploaded song. The thesis describes the principles of machine learning with a focus on convolutional neural networks. A considerable part of this thesis is devoted to the research of available datasets created for the purpose of music information retrieval. Next, the process of preparation of the selected dataset and transformation of audio information into spectrograms for the learning of convolutional neural networks is described. Two models capable of recognizing the genre of music were created as a part of the thesis. First, for general, more popular genres and the second focuses on subgenres of electronic music. The result is a web application that, after a song is uploaded, displays the probabilities of classification into individual genres.
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Analysis of real-time data of public transport vehicles
Čižmář, Filip ; Nečaský, Martin (advisor) ; Svoboda, Martin (referee)
This thesis deals with analysis of real-time data of public transport vehicles over open data in Prague. Its main purpose is to create statistics and improve estimation, based on historical data, of a vehicle delay on its route between reference points. For demonstration of the computed data a front-end web app is created. This interactive app is able to show current vehicles locations over a map and other useful information. All components were tested. Open data from Prague public transport company were used to demonstrate that open data can be used for achieving high goals.
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