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2 Annals of Computer Science and Information Systems

2 Jakubik Jan

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Searching for loops and sound samples with feature learning

Jakubik Jan

Annals of Computer Science and Information Systems

2022

Vol. 31

13--18

In this paper, we evaluate feature learning in the problem of retrieving subjectively interesting sounds from electronic music tracks. We describe an active learning system designed to find sounds categorized as samples or loops. These retrieval tasks originate from a broader R&D project, which concerns the use of machine learning for streamlining the creation of videogame content synchronized with soundtracks. The method is expected to function in the context of limited data availability, and as such cannot rely on supervised learning of what constitutes an "interesting sound''. We apply an active learning procedure that allows us to find sound samples without predefined classes through user interaction, and evaluate the use of neural network feature extraction in the problem.

Retrieving Sound Samples of Subjective Interest With User Interaction

Jakubik Jan

Annals of Computer Science and Information Systems

2020

Vol. 21

387--390

This paper concerns the retrieval of audio samples with a high degree of user interaction, motivated by a practical use case. We consider an open set recognition scenario in which the goal is to find all occurrences of a subjectively interesting sound selected by a user within a particular audio file. We use only a single starting example and maintain interaction through yes-no answers from the user, indicating whether any new retrieved sound matches the target pattern. We present a small dataset for this task and evaluate a baseline solution based on Nonnegative Matrix Factorization and greedy feature selection.