B. Kostek, M. Dziubinski, and P. Zwan, “Further Developments of Methods for Searching Optimum Musical and Rhythmic Feature Vectors,” in Proc. AES Conference: 21st International Conference: Architectural Acoustics and Sound Reinforcement, Jun. 2002, Paper 000068. [Online]. Available: https://aes.org/publications/elibrary-page/?id=11216
Kostek B, Dziubinski M, Zwan P. Further Developments of Methods for Searching Optimum Musical and Rhythmic Feature Vectors. In: AES Conference: 21st International Conference: Architectural Acoustics and Sound Reinforcement. Audio Engineering Society; 2002. Paper 000068. Available from: https://aes.org/publications/elibrary-page/?id=11216
@inproceedings{Kostek2002_11216,
author = {Kostek, Bozena and Dziubinski, Marek and Zwan, Pawel},
title = {{Further Developments of Methods for Searching Optimum Musical and Rhythmic Feature Vectors}},
booktitle = {AES Conference: 21st International Conference: Architectural Acoustics and Sound Reinforcement},
note = {Paper 000068},
year = {2002},
month = jun,
publisher = {Audio Engineering Society},
url = {https://aes.org/publications/elibrary-page/?id=11216}
}
TY - CPAPER
TI - Further Developments of Methods for Searching Optimum Musical and Rhythmic Feature Vectors
AU - Kostek, Bozena
AU - Dziubinski, Marek
AU - Zwan, Pawel
T2 - AES Conference: 21st International Conference: Architectural Acoustics and Sound Reinforcement
M1 - Paper 000068
PY - 2002
DA - 2002/06/06
UR - https://aes.org/publications/elibrary-page/?id=11216
PB - Audio Engineering Society
LA - en
AB - The aim of this paper is first to review recent developments in the domain of musical information retrieval and then to present some methods developed at the Sound and Vision Engineering Department of the Gdansk University of Technology, Poland. Especially important for music retrieval systems is to find optimum music representation. This is can be done using the so-called FED decomposition first. This algorithm is also used for musical duet separation. In this context the evaluation of the efficiency of the FED algorithm based on the ANNs is given. Results of the performed experiments are shown and conclusions are derived.
ER -