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Conference papers
SPARSE MUSIC DECOMPOSITION ONTO A MIDI DICTIONARY DRIVEN BY STATISTICAL MUSIC KNOWLEDGE
Abstract : The general goal of music signal decomposition is to represent the music structure into a note level to provide val- uable semantic features for further music analysis tasks. In this paper, we propose a new method to sparsely decompose the music signal onto a MIDI dictionary made of musical notes. Statistical music knowledge is further integrated into the whole sparse decomposition process. The proposed method is divided into a frame level sparse decomposition stage and a whole music level optimal note path searching. In the first stage note co-occurrence probabilities are embedded to generate a sparse multiple candidate graph while in the second stage note transition probabilities are incorporated into the optimal path searching. Experiments on real-world polyphonic music show that embedding music knowledge within the sparse decomposition achieves notable improvement in terms of note recognition precision and recall.
https://hal.archives-ouvertes.fr/hal-01339270
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Wednesday, June 29, 2016 - 3:51:06 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:45 PM
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Wednesday, June 29, 2016 - 3:51:06 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:45 PM