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Purging Musical Instrument Sample Databases Using Automatic Musical Instrument Recognition Methods

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text
 

Genre(s)

article
 

Forme(s)

document numérique
 

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Titre

Purging Musical Instrument Sample Databases Using Automatic Musical Instrument Recognition Methods
 

Nom(s)

Livshin, Arie (auteur)
 
Rodet, Xavier (auteur)
 

Publication

2009
 

Description

Sujet(s)

musical instruments   Instrument recognition   multimedia databases   music   music information retrieval   pattern classification
 

Résumé

Compilation of musical instrument sample databases requires careful elimination of badly recorded samples and validation of sample classification into correct categories. This paper introduces algorithms for automatic removal of bad instrument samples using Automatic Musical Instrument Recognition and Outlier Detection techniques. Best evaluation results on a methodically contaminated sound database are achieved using the introduced MCIQR method, which removes 70.1% "bad" samples with 0.9% false-alarm rate and 90.4% with 8.8% false-alarm rate.
 

Note(s)

Article paru dans : IEEE Transactions on Audio, Speech, and Language Processing vol. 17 n°5
 

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Date de la notice

2010-02-25 01:00:00
 

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