Influence of Feature Sets on Precision, Recall, and Accuracy of Identification of Musical Instruments in Audio Recordings-Reference-Cited by-同舟云学术

Influence of Feature Sets on Precision, Recall, and Accuracy of Identification of Musical Instruments in Audio Recordings

Published:2014 Issue: Volume: Page:204-213
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Kubera Elżbieta,Wieczorkowska Alicja A.,Skrzypiec Magdalena

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-08326-1_21

Reference27 articles.

1. Barbedo, J.G.A., Tzanetakis, G.: Musical Instrument Classification Using Individual Partials. IEEE Trans. Audio, Speech, Lang. Process. 19(1), 111–122 (2011)

2. Bosch, J.J., Janer, J., Fuhrmann, F., Herrera, P.: A Comparison of Sound Segregation Techniques for Predominant Instrument Recognition in Musical Audio Signals. In: 13th Int. Society for Music Information Retrieval Conf., pp. 559–564 (2012)

3. Breiman, L.: Random Forests. Machine Learning 45, 5–32 (2001)

4. Cont, A., Dubnov, S., Wessel, D.: Realtime multiple-pitch and multiple-instrument recognition for music signals using sparse non-negativity constraints. In: 10th Int. Conf. Digital Audio Effects, pp. 85–92 (2007)

5. Eggink, J., Brown, G.J.: Application of missing feature theory to the recognition of musical instruments in polyphonic audio. In: 4th International Conference on Music Information Retrieval (2003)

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