Skip to Main content Skip to Navigation
Other publications

Two nonnegative matrix factorization methods for polyphonic pitch transcription

Emmanuel Vincent 1 Nancy Bertin 2 Roland Badeau 2
1 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Polyphonic pitch transcription consists of estimating the onset time, duration and pitch of each note within a music signal. Adaptive signal models such as Nonnegative Matrix Factorization (NMF) appear well suited to this task, since they can provide a meaningful representation whatever instruments are playing. In this paper, we propose a simple transcription method using minimum residual loudness NMF, harmonic comb-based pitch identification and threshold-based onset/offset detection, and investigate a second method incorporating harmonicity constraints in the NMF model. Both methods are evaluated in the framework of MIREX 2007.
Complete list of metadata

Cited literature [11 references]  Display  Hide  Download
Contributor : Emmanuel Vincent Connect in order to contact the contributor
Submitted on : Tuesday, December 7, 2010 - 3:01:12 PM
Last modification on : Thursday, January 20, 2022 - 5:28:34 PM
Long-term archiving on: : Tuesday, March 8, 2011 - 4:31:43 AM


Publisher files allowed on an open archive


  • HAL Id : inria-00544213, version 1


Emmanuel Vincent, Nancy Bertin, Roland Badeau. Two nonnegative matrix factorization methods for polyphonic pitch transcription. 2007. ⟨inria-00544213⟩



Les métriques sont temporairement indisponibles