Transcription et séparation automatique de la mélodie principale dans les signaux de musique polyphoniques

Abstract : We propose to address the problem of melody extraction along with the monaural lead instrument and accompaniment separation problem. The first task is related to Music Information Retrieval (MIR), since it aims at indexing the audio music signals with their melody. The separation problem is related to Blind Audio Source Separation (BASS), as it aims at breaking an audio mixture into several source tracks. Leading instrument source separation and main melody extraction are addressed within a unified framework. The lead instrument is modelled thanks to a source/filter production model. Its signal is generated by two hidden states, the filter state and the source state. The proposed signal spectral model therefore explicitly uses pitches both to separate the lead instrument from the others and to transcribe the pitch sequence played by that instrument, the "main melody". This model gives rise to two alternative models, a Gaussian Scaled Mixture Model (GSMM) and the Instantaneous Mixture Model (IMM). The accompaniment is modelled with a more general spectral model. Five systems are proposed. Three systems detect the fundamental frequency sequence of the lead instrument, i.e. they estimate the main melody. A system returns a musical melody transcription and the last system separates the lead instrument from the accompaniment. The results in melody transcription and source separation are at the state of the art, as shown by our participations to international evaluation campaigns (MIREX'08, MIREX'09 and SiSEC'08). The proposed extension of previous source separation works using "MIR" knowledge is therefore a very successful combination.
Document type :
Theses
Domain :
Complete list of metadatas

Cited literature [149 references]  Display  Hide  Download

https://pastel.archives-ouvertes.fr/pastel-00006123
Contributor : Ecole Télécom Paristech <>
Submitted on : Friday, June 4, 2010 - 8:00:00 AM
Last modification on : Wednesday, February 20, 2019 - 2:41:09 PM
Long-term archiving on : Thursday, March 30, 2017 - 5:56:25 AM

Identifiers

  • HAL Id : pastel-00006123, version 1

Citation

Jean-Louis Durrieu. Transcription et séparation automatique de la mélodie principale dans les signaux de musique polyphoniques. domain_other. Télécom ParisTech, 2010. Français. ⟨pastel-00006123⟩

Share

Metrics

Record views

327

Files downloads

493