Purging Musical Instrument Sample Databases Using Automatic Musical Instrument Recognition Methods

Arie Livshin (1) , Xavier Rodet (1)

1 Analyse et synthèse sonores [Paris]

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.

Mots clés: music; musical instruments; Instrument recognition; music information retrieval; multimedia databases; pattern classification

Mots clés: Informatique musicale

Domaines: Acoustique [physics.class-ph]; Traitement du signal et de l'image [eess.SP]; Neurosciences

Arie Livshin, Xavier Rodet. Purging Musical Instrument Sample Databases Using Automatic Musical Instrument Recognition Methods. IEEE Transactions on Audio, Speech and Language Processing, 2009, 17 (5), pp.1046-1051. ⟨hal-01161417⟩