Automatic music transcription is a very actual problem in computer vision and multimedia. There have been many advances in the field, but only recently direct transcription from guitar music to tablatures, which, unlike notes, are not uniform, has been attempted. The goal of this diploma thesis is to make a program, that could estimate a playable and accurate tablature from a given recording of guitar music. For that process, we could use convolutional neural networks. By combining a convolutional and recurrent neural network architecture, we can achieve very good results for the task of automatic guitar transcription.
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