TY - GEN
T1 - SELF-SIMILARITY-BASED AND NOVELTY-BASED LOSS FOR MUSIC STRUCTURE ANALYSIS
AU - Peeters, Geoffroy
N1 - Publisher Copyright:
© G. Peeters.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Music Structure Analysis (MSA) is the task aiming at identifying musical segments that compose a music track and possibly label them based on their similarity. In this paper we propose a supervised approach for the task of music boundary detection. In our approach we simultaneously learn features and convolution kernels. For this we jointly optimize - a loss based on the Self-Similarity-Matrix (SSM) obtained with the learned features, denoted by SSM-loss, and - a loss based on the novelty score obtained applying the learned kernels to the estimated SSM, denoted by novelty-loss. We also demonstrate that relative feature learning, through self-attention, is beneficial for the task of MSA. Finally, we compare the performances of our approach to previously proposed approaches on the standard RWC-Pop, and various subsets of SALAMI.
AB - Music Structure Analysis (MSA) is the task aiming at identifying musical segments that compose a music track and possibly label them based on their similarity. In this paper we propose a supervised approach for the task of music boundary detection. In our approach we simultaneously learn features and convolution kernels. For this we jointly optimize - a loss based on the Self-Similarity-Matrix (SSM) obtained with the learned features, denoted by SSM-loss, and - a loss based on the novelty score obtained applying the learned kernels to the estimated SSM, denoted by novelty-loss. We also demonstrate that relative feature learning, through self-attention, is beneficial for the task of MSA. Finally, we compare the performances of our approach to previously proposed approaches on the standard RWC-Pop, and various subsets of SALAMI.
M3 - Conference contribution
AN - SCOPUS:85209540792
T3 - 24th International Society for Music Information Retrieval Conference, ISMIR 2023 - Proceedings
SP - 749
EP - 756
BT - 24th International Society for Music Information Retrieval Conference, ISMIR 2023 - Proceedings
A2 - Sarti, Augusto
A2 - Antonacci, Fabio
A2 - Sandler, Mark
A2 - Bestagini, Paolo
A2 - Dixon, Simon
A2 - Liang, Beici
A2 - Richard, Gael
A2 - Pauwels, Johan
PB - International Society for Music Information Retrieval
T2 - 24th International Society for Music Information Retrieval Conference, ISMIR 2023
Y2 - 5 November 2023 through 9 November 2023
ER -