Project detail

Identification of the Czech origin of digital music recordings using machine learning

Duration: 01.02.2021 — 31.01.2023

Funding resources

Evropská unie - Interní grantová soutěž

- whole funder (2021-02-01 - 2023-01-31)

On the project

The project aims to create a classifier that will be able to differentiate the string quartet recordings of Czech performers from the rest of Europe/world. The key is to find the parameters of digital recordings (e.g. MPEG-7 parameters), which characterize Czech production. Machine learning will be used for the analysis—k-NN and clustering for the parametrization and convolutional neural networks (CNNs) for the classification. The project builds on the previous thesis of the main proposer, where the potential of this research was identified.

Mark

FEKT-K-21-6874

Default language

English

People responsible

Miklánek Štěpán, Ing., Ph.D. - fellow researcher
Ištvánek Matěj, Ing., Ph.D. - principal person responsible

Units

Department of Telecommunications
- co-beneficiary (2021-02-01 - 2023-01-31)
Faculty of Electrical Engineering and Communication
- beneficiary (2021-02-01 - 2023-01-31)

Results

IŠTVÁNEK, M.; MIKLÁNEK, Š. Exploring the Possibilities of Automated Annotation of Classical Music with Abrupt Tempo Changes. In Proceedings II of the 28th Conference STUDENT EEICT 2022 Selected Papers. 1. Brno: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2022. p. 286-290. ISBN: 978-80-214-6030-0.
Detail

IŠTVÁNEK, M.; MIKLÁNEK, Š. Towards Automatic Measure-Wise Feature Extraction Pipeline for Music Performance Analysis. In 45th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2022. p. 192-195. ISBN: 978-1-6654-6948-7.
Detail

IŠTVÁNEK, M.; MIKLÁNEK, Š.; SPURNÝ, L. Classification of Interpretation Differences in String Quartets Based on the Origin of Performers. Applied Sciences - Basel, 2023, vol. 13, no. 6, p. 1-20. ISSN: 2076-3417.
Detail

ÖZER, Y.; IŠTVÁNEK, M.; ARIFI-MÜLLER, V.; MÜLLER, M. Using Activation Functions for Improving Measure-Level Audio Synchronization. Proceedings of the International Society for Music Information Retrieval Conference (ISMIR). 2022. p. 750-756.
Detail

NOVÁK, V. Proceedings I of the 28th Conference STUDENT EEICT 2022 General papers. Proceedings I of the 28th Conference STUDENT EEICT 2022 General papers. 1. Brno: Brno University of Technology, Faculty of Electrical Engineering and Communication, 2022. ISBN: 978-80-214-6029-4.
Detail

Responsibility: Ištvánek Matěj, Ing., Ph.D.