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Application for Online Music Notation Typesetting
Mackovič, Jakub ; Rychlý, Marek (referee) ; Burget, Radek (advisor)
In this thesis, an application for musical notation in the environment of web browsers using the SVG vector graphics format is proposed. We have a look at relevant standard notation practices as well as at the history of musical typesetting. Existing programs for musical notation are classified and examined and based on those a user interface for the application is designed along with some modifications. The implementation of the application is then described. A set of features is presented and their usefulness is with the user interface tested on users. The feedback of the testing is then evaluated and the application is improved based on the feedback. Finally, the future of the application is discussed. Because SVG can still be considered an experimental technology and many browsers lack its support or their behaviour differs, the application is only guaranteed to work on the Google Chrome browser.
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Automatic recognition of musical notation from audio data
Čermák, Marek ; Lokoč, Jakub (advisor) ; Hajič, Jan (referee)
Title: Automatic recognition of musical notation from audio data Author: Marek Čermák Department: Department of Software Engineering Supervisor: doc. RNDr. Jakub Lokoč, Ph.D. Abstract: The goal of this thesis is the design and implementation of an application using convolutional neural networks to generate musical notation from audio data. The application is able to train a neural network using input files in the MIDI (Musical Instrument Digital Interface) format and pair all sections of the music with their audio form. The training of the neural network can be performed on a user- specified collection of MIDI files or on randomly generated music. Each instrument in the MIDI standard can be assigned a network whose output are the notes playing in the given time section. Continuously iterating over the audio data, the network generates sections of active notes which are then concatenated into the output file. The application is also capable of recognizing words from audio using an external service. Keywords: musical notation, neural network, deep learning, audio recognition, MIDI
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Application for Online Music Notation Typesetting
Mackovič, Jakub ; Rychlý, Marek (referee) ; Burget, Radek (advisor)
In this thesis, an application for musical notation in the environment of web browsers using the SVG vector graphics format is proposed. We have a look at relevant standard notation practices as well as at the history of musical typesetting. Existing programs for musical notation are classified and examined and based on those a user interface for the application is designed along with some modifications. The implementation of the application is then described. A set of features is presented and their usefulness is with the user interface tested on users. The feedback of the testing is then evaluated and the application is improved based on the feedback. Finally, the future of the application is discussed. Because SVG can still be considered an experimental technology and many browsers lack its support or their behaviour differs, the application is only guaranteed to work on the Google Chrome browser.
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