A Survey on Musical Feature Extraction and Classification Methods

Authors

  • Patel Prem  U.G. Student, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Prajapati Akshay  U.G. Student, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Gandhi Abhi  U.G. Student, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Pandya Mehul  U.G. Student, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Mrs. Mahajan Arpana  U.G. Student, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Dr. Sheshang Degadwala  Head of Department, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India

DOI:

https://doi.org//10.32628/CI008

Keywords:

Musical instruments, Musical Features, Rhythm, Temporal, Musical Classifier

Abstract

Identifying musical instrument is challenging task because of its multidimensional nature. Every particular instruments have its own characteristics and physical features like energy feature, rhythm feature, temporal feature, spectrum feature, harmony feature etc. In this paper toolboxes that are all publically available for extracting these features. & the perception of valance and arousal has been also discussed. This paper offers an overview of the set of upper features. Particular attention has been paid to design of a syntax that offers both simplicity of use & transparent addictiveness to a multiplicity of possible input also the same syntax can be used for analysis of signal audio files, batch files, series of audio segments multi banned signals. Also we have studied about the preprocessing and automatic speech recognition the preprocessing is done and voice speech is detected based on energy and zero crossing rates.

References

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Published

2018-04-10

Issue

Section

Research Articles

How to Cite

[1]
Patel Prem, Prajapati Akshay, Gandhi Abhi, Pandya Mehul, Mrs. Mahajan Arpana, Dr. Sheshang Degadwala, " A Survey on Musical Feature Extraction and Classification Methods, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 5, pp.278-282, March-April-2018. Available at doi : https://doi.org/10.32628/CI008