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Automatic music transcription
Matoušek, Vojtěch ; Richter, Miloslav (referee) ; Petyovský, Petr (advisor)
This article deals with the automatic music transcription into the music notation by Fourier transform with logarithmic scale and constant Q transform. The result of this work is application, which converts the music records, in the WAVE music le, into the MIDI le. Then MIDI le can convert into the music notation by appropriate tool. Algorithm for automatic music transcription can converts polyphonic music record, where plays more tones at one time, with simple rhythm.
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Tool for Piano Practising
Ustinov, Nikita ; Hrubý, Martin (referee) ; Zbořil, František (advisor)
The purpose of this work is to design and implement an application for piano practice. The main disadvantage of existing applications is the limited selection of songs that can be practiced. The application, which is the result of this work, will solve the problem - the user will be able to upload to the application any piano record he wants to practice, and the application will take care of creating a training process. The training process consists of showing the user a certain way of editing notes and simultaneously controlling what the user is playing with a microphone. The biggest challenge of the diploma thesis was to find a way to accurately and quickly classify the audio signal from the microphone. This problem was solved using two independent neural networks with different architectures, which were trained on different data sets. To justify the chosen solution, all the necessary theoretical musical and scientific concepts and methods that are directly related to it will be presented. The resulting application will be tested in three respects: accuracy, speed, the usability of the user.
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Conversion of Piano Recording from WAV to MIDI
Bednařík, Jan ; Černocký, Jan (referee) ; Szőke, Igor (advisor)
The aim of the thesis is to propose a system capable of automatic conversion of polyphonic piano recordings from the audio format WAV to MIDI. The thesis describes problems related to single tone recognition in music recordings and proposes a solution based on a probabilistic model that uses the Probabilistic Latent Component Analysis method. Recordings of isolated digital piano tones were used to train the system. The proposed system was tested on classical recordings of the Classical Piano MIDI database and on recordings of a Korg SP-250 piano and evaluated using a variety of metrics. The conclusion part contains the results of recognition success rate and their comparison with other existing systems.
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Tool for Piano Practising
Ustinov, Nikita ; Hrubý, Martin (referee) ; Zbořil, František (advisor)
The purpose of this work is to design and implement an application for piano practice. The main disadvantage of existing applications is the limited selection of songs that can be practiced. The application, which is the result of this work, will solve the problem - the user will be able to upload to the application any piano record he wants to practice, and the application will take care of creating a training process. The training process consists of showing the user a certain way of editing notes and simultaneously controlling what the user is playing with a microphone. The biggest challenge of the diploma thesis was to find a way to accurately and quickly classify the audio signal from the microphone. This problem was solved using two independent neural networks with different architectures, which were trained on different data sets. To justify the chosen solution, all the necessary theoretical musical and scientific concepts and methods that are directly related to it will be presented. The resulting application will be tested in next respects: accuracy, speed, noise resistance and the usability of the user.
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Electric Guitar to MIDI Conversion
Klčo, Michal ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
Automatický přepis hudby a odhad vícero znějících tónu jsou stále výzvou v oblasti dolování informací z hudby. Moderní systémy jsou založeny na různých technikách strojového učení pro dosažení co nejpřesnějšího přepisu hudby. Některé z nich jsou také omezeny na konkrétní hudební nástroj nebo hudební žánr, aby se snížila rozmanitost analyzovaného zvuku. V této práci je navrženo, vyhodnoceno a porovnáváno několik systémů pro konverzi nahrávek elektrické kytary do MIDI souború, založených na různých technikách strojového učení a technikách spektrální analýzy.
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Tool for Piano Practising
Ustinov, Nikita ; Hrubý, Martin (referee) ; Zbořil, František (advisor)
The purpose of this work is to design and implement an application for piano practice. The main disadvantage of existing applications is the limited selection of songs that can be practiced. The application, which is the result of this work, will solve the problem - the user will be able to upload to the application any piano record he wants to practice, and the application will take care of creating a training process. The training process consists of showing the user a certain way of editing notes and simultaneously controlling what the user is playing with a microphone. The biggest challenge of the diploma thesis was to find a way to accurately and quickly classify the audio signal from the microphone. This problem was solved using two independent neural networks with different architectures, which were trained on different data sets. To justify the chosen solution, all the necessary theoretical musical and scientific concepts and methods that are directly related to it will be presented. The resulting application will be tested in next respects: accuracy, speed, noise resistance and the usability of the user.
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|
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Tool for Piano Practising
Ustinov, Nikita ; Hrubý, Martin (referee) ; Zbořil, František (advisor)
The purpose of this work is to design and implement an application for piano practice. The main disadvantage of existing applications is the limited selection of songs that can be practiced. The application, which is the result of this work, will solve the problem - the user will be able to upload to the application any piano record he wants to practice, and the application will take care of creating a training process. The training process consists of showing the user a certain way of editing notes and simultaneously controlling what the user is playing with a microphone. The biggest challenge of the diploma thesis was to find a way to accurately and quickly classify the audio signal from the microphone. This problem was solved using two independent neural networks with different architectures, which were trained on different data sets. To justify the chosen solution, all the necessary theoretical musical and scientific concepts and methods that are directly related to it will be presented. The resulting application will be tested in three respects: accuracy, speed, the usability of the user.
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Automatic Music Transcription
Matoušek, Vojtěch
This article deals with the automatic music transcription into the music notation by short Fourier transform with logarithmic scale. The result of this work is application, which converts the music records, in the wave file, into the music notation. But the algorithm can work only with music records, where plays one tone at one time.
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Electric Guitar to MIDI Conversion
Klčo, Michal ; Glembek, Ondřej (referee) ; Černocký, Jan (advisor)
Automatický přepis hudby a odhad vícero znějících tónu jsou stále výzvou v oblasti dolování informací z hudby. Moderní systémy jsou založeny na různých technikách strojového učení pro dosažení co nejpřesnějšího přepisu hudby. Některé z nich jsou také omezeny na konkrétní hudební nástroj nebo hudební žánr, aby se snížila rozmanitost analyzovaného zvuku. V této práci je navrženo, vyhodnoceno a porovnáváno několik systémů pro konverzi nahrávek elektrické kytary do MIDI souború, založených na různých technikách strojového učení a technikách spektrální analýzy.
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Automatic music transcription
Matoušek, Vojtěch ; Richter, Miloslav (referee) ; Petyovský, Petr (advisor)
This article deals with the automatic music transcription into the music notation by Fourier transform with logarithmic scale and constant Q transform. The result of this work is application, which converts the music records, in the WAVE music le, into the MIDI le. Then MIDI le can convert into the music notation by appropriate tool. Algorithm for automatic music transcription can converts polyphonic music record, where plays more tones at one time, with simple rhythm.
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