Comparing Voice and Stream Segmentation Algorithms
Document type :
Communication dans un congrès avec actes
Title :
Comparing Voice and Stream Segmentation Algorithms
Author(s) :
Guiomard-Kagan, Nicolas [Auteur]
Algomus
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Giraud, Mathieu [Auteur]
Algomus
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Groult, Richard [Auteur]
Algomus
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Leve, Florence [Auteur]
Algomus
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Algomus
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Giraud, Mathieu [Auteur]
Algomus
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Groult, Richard [Auteur]
Algomus
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Leve, Florence [Auteur]
Algomus
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Modélisation, Information et Systèmes - UR UPJV 4290 [MIS]
Conference title :
International Society for Music Information Retrieval Conference (ISMIR 2015)
City :
Malaga
Country :
Espagne
Start date of the conference :
2015-10-26
Book title :
Proceedings of the 16th ISMIR Conference
Publication date :
2015
English keyword(s) :
stream segmentation
voice segmentation
music information retrieval
melody
voice segmentation
music information retrieval
melody
HAL domain(s) :
Sciences de l'Homme et Société/Musique, musicologie et arts de la scène
Informatique [cs]/Son [cs.SD]
Informatique [cs]/Algorithme et structure de données [cs.DS]
Informatique [cs]/Son [cs.SD]
Informatique [cs]/Algorithme et structure de données [cs.DS]
English abstract : [en]
Voice and stream segmentation algorithms group notes from polyphonic data into relevant units, providing a better understanding of a musical score. Voice segmentation algorithms usually extract voices from the beginning ...
Show more >Voice and stream segmentation algorithms group notes from polyphonic data into relevant units, providing a better understanding of a musical score. Voice segmentation algorithms usually extract voices from the beginning to the end of the piece, whereas stream segmentation algorithms identify smaller segments. In both cases, the goal can be to obtain mostly monophonic units, but streams with poly-phonic data are also relevant. These algorithms usually cluster contiguous notes with close pitches. We propose an independent evaluation of four of these algorithms (Tem-perley, Chew and Wu, Ishigaki et al., and Rafailidis et al.) using several evaluation metrics. We benchmark the algorithms on a corpus containing the 48 fugues of Well-Tempered Clavier by J. S. Bach as well as 97 files of popular music containing actual polyphonic information. We discuss how to compare together voice and stream segmen-tation algorithms, and discuss their strengths and weaknesses.Show less >
Show more >Voice and stream segmentation algorithms group notes from polyphonic data into relevant units, providing a better understanding of a musical score. Voice segmentation algorithms usually extract voices from the beginning to the end of the piece, whereas stream segmentation algorithms identify smaller segments. In both cases, the goal can be to obtain mostly monophonic units, but streams with poly-phonic data are also relevant. These algorithms usually cluster contiguous notes with close pitches. We propose an independent evaluation of four of these algorithms (Tem-perley, Chew and Wu, Ishigaki et al., and Rafailidis et al.) using several evaluation metrics. We benchmark the algorithms on a corpus containing the 48 fugues of Well-Tempered Clavier by J. S. Bach as well as 97 files of popular music containing actual polyphonic information. We discuss how to compare together voice and stream segmen-tation algorithms, and discuss their strengths and weaknesses.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
ANR Project :
Collections :
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