Detailed Information on Publication Record
2019
Enhancement of Beat Tracking in String Quartet Music Analysis Based on the Teager-Kaiser Energy Operator
SPURNÝ, Lubomír, Matěj IŠTVANEK, Jiří MEKYSKA and Zdeněk SMÉKALBasic information
Original name
Enhancement of Beat Tracking in String Quartet Music Analysis Based on the Teager-Kaiser Energy Operator
Authors
SPURNÝ, Lubomír, Matěj IŠTVANEK, Jiří MEKYSKA and Zdeněk SMÉKAL
Edition
42nd International Conference on Telecommunications and Signal Processing (TSP), 2019
Other information
Language
English
Type of outcome
Konferenční abstrakt
Field of Study
60403 Performing arts studies
Country of publisher
Hungary
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Organization unit
Faculty of Arts
Keywords in English
audio signal processing;information retrieval;music;signal detection;string quartet music analysis
Tags
International impact, Reviewed
Změněno: 26/4/2020 00:05, prof. PhDr. Lubomír Spurný, Ph.D.
Abstract
V originále
Beat detection systems are widely used in music information retrieval (MIR) research field for the computation of tempo and beat positions in audio signals. One of the most important parts of these systems is the onset detection function. The aim of this study is to introduce an enhancement of a conventional onset detector and employ it in a beat tracking system that could be utilized for an analysis of interpretation and performance changes in string quartets. The enhancement is based on the Teager-Kaiser energy operator (TKEO), which pre-processes input audio signal before spectral flux calculation. The proposed approach is firstly evaluated in terms of ability to estimate global tempo (GT) of a given audio track. Next, the accuracy of the GT estimation is compared with a manually-labelled reference dataset. Then, this system was tested on the first motif of the string quartet database. Results suggest that the TKEO could improve accuracy of the GT estimation. Average deviation from the reference tempo in the string quartet is 8.29%, which slightly improves the conventional methodology, where the deviance is 8.96%. This study has a pilot character and provides some suggestions of the beat tracking system enhancement.