Score-informed source separation for multichannel orchestral recordings

This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good alignment of the score with the audio of the performance. To that extent, aut...

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Detalhes bibliográficos
Autores: Miron, Marius, Carabias Orti, Julio J., Bosch, Juan J., Gómez Gutiérrez, Emilia, 1975-, Janer Mestres, Jordi
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2016
País:España
Recursos:Universitat Pompeu Fabra
Repositório:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/32186
Acesso em linha:http://hdl.handle.net/10230/32186
http://dx.doi.org/10.1155/2016/8363507
Access Level:Acceso aberto
Palavra-chave:So -- Enregistrament i reproducció
Enginyeria acústica
Descrição
Resumo:This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good alignment of the score with the audio of the performance. To that extent, automatic score alignment methods are reliable when allowing a tolerance window around the actual onset and offset. Moreover, several factors increase the difficulty of our task: a high reverberant image, large ensembles having rich polyphony, and a large variety of instruments recorded within a distant-microphone setup. To solve these problems, we design context-specific methods such as the refinement of score-following output in order to obtain a more precise alignment. Moreover, we extend a close-microphone separation framework to deal with the distant-microphone orchestral recordings. Then, we propose the first open evaluation dataset in this musical context, including annotations of the notes played by multiple instruments from an orchestral ensemble. The evaluation aims at analyzing the interactions of important parts of the separation framework on the quality of separation. Results show that we are able to align the original score with the audio of the performance and separate the sources corresponding to the instrument sections.