Title

Hybridisation of Mel Frequency Cepstral Coefficient and Higher Order Spectral Features for Musical Instruments Classification

Journal title

Archives of Acoustics

Yearbook

2016

Volume

vol. 41

Issue

No 3

Authors

Bhalke, Daulappa Guranna ; Rao, C. B. Rama ; Bormane, Dattatraya

Keywords

feature extraction ; MFCC ; HOS ; bispectrum ; bicoherence ; non-linearity ; non-Gaussianity ; CPNN ; Zero Crossing Rate (ZCR)

Divisions of PAS

Nauki Techniczne

Coverage

427-436

Publisher

Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics

Date

2016

Type

Artykuły / Articles

Identifier

DOI: 10.1515/aoa-2016-0042

Source

Archives of Acoustics; 2016; vol. 41; No 3; 427-436

References

Kostek (2008), Music information analysis and retrieval techniques of Acoustics, Archives, 33, 483. ; Ajmera (2012), Robust feature extraction from spectrum estimated using Bispectrum for speaker recognition of Speech Technology, Int Journal, 15, 433. ; Eronen (2000), Musical Instrument Recognition using cepstral coefficients and temporal features in of IEEE International Conference on Acoustics Speech and Signal Processing, Proc, 2, 753756. ; Kostek (2004), Application of soft computing to automatic music information retrieval of American Society for Information Science and Technology, Journal, 55, 12. ; Kostek (2004), Musical instrument classification and duet analysis employing music information retrieval techniques, Proc IEEE, 92, 712, doi.org/10.1109/JPROC.2004.825903 ; Kostek (1997), Parametric representation of musical sounds of Acoustics, Archives, 22, 1. ; Kostek (2001), Representing musical instrument sounds for their automatic classification of Audio Engineering, Journal Society, 49, 768. ; Byun (2002), Applications of support vector machines for pattern recognition in of the International Workshop on Pattern Recognition with Support Vector Machine pp, Proc, 213. ; Dubnov (2003), Investigation of phase coupling phenomena in sustained portion of musical instruments sound, Soc Am, 113. ; Goppert (1993), Self - organizing maps vs back - propagation : An experimental study of pp, Proc Work Design Methodol Microelectron Signal Process, 153. ; Goshvarpour (2012), Bispectrum Estimation of Electroencephalogram Signal During Meditation, Psychiatry Behav Sci, 6. ; Kostek (1997), Application of artificial neural networks to the recognition of musical sounds of Acoustics, Archives, 22, 1. ; Kaminskyj (2005), Automatic Recognition of Isolated Monophonic Musical Instrument Sounds using kNNC of Intelligent Information Systems, Journal, 24, 199. ; Bordolois (2012), Classification of Motor imagery based on Hybrid features of Bispectrum of EEG International Conference on Communications Devices and Intelligent Systems pp, IEEE, 123. ; Agostini (2003), Musical instrument timbre classification with spectral features, Appl Signal Process, 1. ; Essid (2006), Hierarchical Classification of Musical Instruments on Solo Recordings in of IEEE International Conference on Acoustics Speech and Signal Processing, Proc, 5, 14. ; Kostek (2007), Applying computational intelligence to musical acoustics of Acoustics, Archives, 32, 617. ; Bhalke (2014), Musical Instrument Classification using Higher Order Spectra International Conference on Signal Processing and Integrated Networks Feb, SPIN, 20, 2014. ; Liu (2010), Excitation signature extraction for pitched musical instrument timbre analysis using Higher Order Statistics International Conference on Multimedia and Expo, IEEE, 19, 5582571.