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

  1. Swati D. Patil, Tareek M. Pattewar, PG Student, Department of Computer Engineering, SES’s R.C. Patel Institute of Technology, Shirpur, Maharashtra, India, Assistant Professor, Department of Information Technology, SES’s R.C. Patel Institute of Technology, Shirpur, Maharashtra, India; MUSICAL INSTRUMENT IDENTIFICATION USING SVM & MLP WITH FORMAL CONCEPT ANALYSIS.
  2. Olivier Lartillot, Petri Toiviainen, University of Jyvaskyla Finland; A MATLAB TOOLBOX FOR MUSICAL FEATURES EXTRACTION FROM AUDIO. 
  3. Mayur R Gamit, Pro. Kinnal Dhameliya, M.Tech Research Student, Assistant Professor, C.G.P.I.T, Bardoli, India; ENGLISH DIGITS RECOGNITION USING MFCC, LPC AND PEARSON’S CORRELATION
  4. Yading Song, Simon Dixon, Marcus Pearce, Centre for Digital Music, Queen Mary University of London; EVALUATION OF MUSICAL FEATURES FOR EMOTION CLASSIFICATION.
  5. Babu Kaji Baniya and Choong Seon Hong, Department of Computer Engineering Kyung Hee University; MUSIC MOOD CLASSIFICATION USING REDUCED AUDIO FEATURES.
  6. I. Nabney, Springer Advances In Pattern Recognition Series, chapter NETLAB: ALGORITHM FOR PATTERN RECOGNITION.
  7. Xian Tang, Pacific – Asia Conference on Circuits, Communication and System, IEEE Computer Society 2009; HYBRID HIDDEN MARKOV MODEL AND ARTIFICIAL NEURAL NETWORK FOR AUTOMATIC SPEECH RECOGNITION.
  8. Nidhi Desai, Prof. Kinnal Dhameliya, International Journal of Emerging Technology And Advance Engineering (IJETAE), Vol 3, Issue 12, December 2013; FEATURE EXTRACTION AND CLASSIFICATION TECHNIQUES FOR SPEECH RECOGNITION.
  9. R. Panda, R. Malheiro, B.Rocha, A. Oliveira and R.P.Paiva, International Symposium on Computer Music Multidisciplinary Research 2013; MULTI - MODEL MUSIC EMOTION RECOGNITION.
  10. Zengchang Qin, Wei Liu, Tao Wan, Inte1lligent Computing and Machine Learning Lab School of ASEE, Beihang University, Beijing, 100191, China, Case Western Reserve University, Cleveland, OH 44106, USA; A BAG OF TONES MODEL WITH MFCC FEATURES FOR MUSICAL GENRE CLASSIFICATION

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-04-10

Issue

Volume 4, Issue 5, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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