Referenced Items are not available for this document.
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.
Published in:
Audio, Speech, and Language Processing, IEEE Transactions on
(Volume:17
,
Issue:
5
)
Date of Publication: July 2009
- Page(s):
- 1046 - 1051
- ISSN :
- 1558-7916
- INSPEC Accession Number:
- 10713580
- Digital Object Identifier :
- 10.1109/TASL.2009.2018439
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 05 June 2009
- Issue Date :
- July 2009
- Sponsored by :
- IEEE Signal Processing Society
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