Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/2422Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Bhalke, D.G. | - |
| dc.contributor.author | Rama Rao, C.B | - |
| dc.contributor.author | Bormane, D.S. | - |
| dc.date.accessioned | 2025-01-06T05:05:18Z | - |
| dc.date.available | 2025-01-06T05:05:18Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.citation | 10.1109/spin.2014.6776918 | en_US |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/2422 | - |
| dc.description | NITW | en_US |
| dc.description.abstract | This paper presents classification and recognition of monophonic isolated musical instrument sounds using higher order spectra such as Bispectrum and Trispectrum. Experimental results on a widely used dataset shows that higher order spectra based features improve the recognition accuracy, when combined with conventional features such as Mel Frequency Cepstral Coefficient (MFCC), Cepstral, Spectral and Temporal features. Nineteen western musical instruments covering four families with full pitch range have been used for experimentation. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | 2014 International Conference on Signal Processing and Integrated Networks, SPIN 2014 | en_US |
| dc.subject | Bispectrum, | en_US |
| dc.subject | Trispectrum, | en_US |
| dc.title | Musical Instrument Classification using Higher Order Spectra | en_US |
| dc.type | Other | en_US |
| Appears in Collections: | Electronics and Communication Engineering | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Musical_instrument_classification_using_higher_order_spectra.pdf | 314.11 kB | Adobe PDF | View/Open |
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