Classification of Interpretation Differences in String Quartets Based on the Origin of Performers

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14210%2F23%3A00134454" target="_blank" >RIV/00216224:14210/23:00134454 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26220/23:PU147878

Výsledek na webu

<a href="https://www.mdpi.com/2076-3417/13/6/3603" target="_blank" >https://www.mdpi.com/2076-3417/13/6/3603</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app13063603" target="_blank" >10.3390/app13063603</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Interpretation Differences in String Quartets Based on the Origin of Performers

Popis výsledku v původním jazyce

Music Information Retrieval aims at extracting relevant features from music material, while Music Performance Analysis uses these features to perform semi-automated music analysis. Examples of interdisciplinary cooperation are, for example, various classification tasks—from recognizing specific performances, musical structures, and composers to identifying music genres. However, some classification problems have not been addressed yet. In this paper, we focus on classifying string quartet music interpretations based on the origin of performers. Our dataset consists of string quartets from composers A. Dvořák, L. Janáček, and B. Smetana. After transferring timing information from reference recordings to all target recordings, we apply feature selection methods to rank the significance of features. As the main contribution, we show that there are indeed origin-based tempo differences, distinguishable by measure durations, by which performances may be identified. Furthermore, we train a machine learning classifier to predict the performers’ origin. We evaluate three different experimental scenarios and achieve higher classification accuracy compared to the baseline using synchronized measure positions.

Název v anglickém jazyce

Classification of Interpretation Differences in String Quartets Based on the Origin of Performers

Popis výsledku anglicky

Music Information Retrieval aims at extracting relevant features from music material, while Music Performance Analysis uses these features to perform semi-automated music analysis. Examples of interdisciplinary cooperation are, for example, various classification tasks—from recognizing specific performances, musical structures, and composers to identifying music genres. However, some classification problems have not been addressed yet. In this paper, we focus on classifying string quartet music interpretations based on the origin of performers. Our dataset consists of string quartets from composers A. Dvořák, L. Janáček, and B. Smetana. After transferring timing information from reference recordings to all target recordings, we apply feature selection methods to rank the significance of features. As the main contribution, we show that there are indeed origin-based tempo differences, distinguishable by measure durations, by which performances may be identified. Furthermore, we train a machine learning classifier to predict the performers’ origin. We evaluate three different experimental scenarios and achieve higher classification accuracy compared to the baseline using synchronized measure positions.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20202 - Communication engineering and systems

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Applied Sciences-Basel

ISSN

2076-3417

e-ISSN

—

Svazek periodika

13

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

20

Strana od-do

1-20

Kód UT WoS článku

000957406100001

EID výsledku v databázi Scopus

2-s2.0-85151551951