Polyphonic pitch estimation and instrument identification by joint modeling of sustained and attack sounds

Abstract : Polyphonic pitch estimation and musical instrument identification are some of the most challenging tasks in the field of Music Information Retrieval (MIR). While existing approaches have focused on the modeling of harmonic partials, we design a joint Gaussian mixture model of the harmonic partials and the inharmonic attack of each note. This model encodes the power of each partial over time as well as the spectral envelope of the attack part. We derive an Expectation-Maximization (EM) algorithm to estimate the pitch and the parameters of the notes. We then extract timbre features both from the harmonic and the attack part via Principal Component Analysis (PCA) over the estimated model parameters. Musical instrument recognition for each estimated note is finally carried out with a Support Vector Machine (SVM) classifier. Experiments conducted on mixtures of isolated notes as well as real-world polyphonic music show higher accuracy over state-of-the-art approaches based on the modeling of harmonic partials only.
Type de document :
Article dans une revue
IEEE Journal of Selected Topics in Signal Processing, IEEE, 2011, 5 (6), pp.1124-1132
Liste complète des métadonnées

Littérature citée [29 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00594965
Contributeur : Emmanuel Vincent <>
Soumis le : mercredi 1 juin 2011 - 18:46:28
Dernière modification le : vendredi 16 novembre 2018 - 01:21:51
Document(s) archivé(s) le : vendredi 2 septembre 2011 - 02:30:57

Fichier

wu_JSTSP11.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inria-00594965, version 2

Citation

Jun Wu, Emmanuel Vincent, Stanislaw Raczynski, Takuya Nishimoto, Nobutaka Ono, et al.. Polyphonic pitch estimation and instrument identification by joint modeling of sustained and attack sounds. IEEE Journal of Selected Topics in Signal Processing, IEEE, 2011, 5 (6), pp.1124-1132. 〈inria-00594965v2〉

Partager

Métriques

Consultations de la notice

572

Téléchargements de fichiers

283