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Emerging Technologies in Data Mining and Information Security pp 181–191Cite as

Stratification of String Instruments Using Chroma-Based Features

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 755))

Abstract

Identification of instrument type from acoustic signal is a challenging issue. It is also an interesting and popular research area having several promising applications in music industry. Researchers have already been able to classify instruments into several broad categories like String, Woodwind, Percussion, and Keyboard etc. using acoustic features like Mel-Frequency Cepstral Coefficients (MFCCs), Zero Crossing Rate (ZCR) etc. MFCC has been found to be excessively used. In this work an alternative acoustic feature of MFCC has been proposed. Chroma is an octave independent estimation of strength of all possible notes in Western 12 note scale at different points of time. Sound envelope originated by a note reflects the signature of an instrument and this can be used to stratify String instruments into various categories. The proposed work relies on Chroma-based low-dimensional feature vector to categorize String instruments. For classification purpose, simple and popular classifiers like Neural Network, k-NN, Naïve Bayes’ have been exercised.

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Author information

Authors and Affiliations

  1. Department of Information Technology, St. Thomas’ College of Engineering & Technology, Kolkata, 700023, West Bengal, India

    Arijit Ghosal

  2. Department of Information Technology and Mathematics, Royal Thimphu College, Thimphu, Bhutan

    Suchibrota Dutta

  3. Department of Management Information Systems, Sarva Siksha Mission, Kolkata, 700042, West Bengal, India

    Debanjan Banerjee

Authors
  1. Arijit Ghosal
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  2. Suchibrota Dutta
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  3. Debanjan Banerjee
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Corresponding authors

Correspondence to Arijit Ghosal or Suchibrota Dutta .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer and Systems Sciences, Visva-Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Computer Science and Engineering, University of Kalyani, Kalyani, India

    Jyotsna Kumar Mandal

  4. Institute of Engineering and Management, Kolkata, West Bengal, India

    Abhishek Bhattacharya

  5. Institute of Engineering and Management, Kolkata, West Bengal, India

    Soumi Dutta

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Ghosal, A., Dutta, S., Banerjee, D. (2019). Stratification of String Instruments Using Chroma-Based Features. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_17

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