Retrieving Sound Samples of Subjective Interest With User Interaction

• Autorzy: Jakubik Jan

Identyfikatory

DOI

10.15439/2020F82

• Konferencja: Federated Conference on Computer Science and Information Systems (15 ; 06-09.09.2020 ; Sofia, Bulgaria)
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

music information retrieval; matrix decomposition; active learning

PL

wyszukiwanie informacji; muzyka; rozkład macierzy; aktywne uczenie się

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2020
• Tom: Vol. 21
• Strony: 387--390
• Opis fizyczny: Bibliogr. 15 poz., wykr., wz.

Twórcy

autor

Jakubik Jan

• Department of Computational Intelligence, Wroclaw University of Science and Technology

Bibliografia

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• [15] Fabian Pedregosa, Ga¨el Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al. Scikit-learn: Machine learning in python. the Journal of machine Learning research, 12:2825-2830, 2011.

Uwagi

1. Track 2: Computer Science & Systems

2. Technical Session: Advances in Computer Science & Systems

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).