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International Conference on Software Engineering and Computer Systems

ICSECS 2011: Software Engineering and Computer Systems pp 724–737Cite as

Recognizing Patterns of Music Signals to Songs Classification Using Modified AIS-Based Classifier

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 180))

Abstract

Human capabilities of recognizing different type of music and grouping them into categories of genre are so remarkable that experts in music can perform such classification using their hearing senses and logical judgment. For decades now, the scientific community were involved in research to automate the human process of recognizing genre of songs. These efforts would normally imitate the human method of recognizing the music by considering every essential component of the songs from artist voice, melody of the music through to the type of instruments used. As a result, various approaches or mechanisms are introduced and developed to automate the classification process. The results of these studies so far have been remarkable yet can still be improved. The aim of this research is to investigate Artificial Immune System (AIS) domain by focusing on the modified AIS-based classifier to solve this problem where the focuses are the censoring and monitoring modules. In this highlight, stages of music recognition are emphasized where feature extraction, feature selection, and feature classification processes are explained. Comparison of performances between proposed classifier and WEKA application is discussed.

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Author information

Authors and Affiliations

  1. Faculty of Information and Communication Technology, University of Technical Malaysia Melaka (UteM), Malaysia

    Noor Azilah Draman, Sabrina Ahmad & Azah Kamilah Muda

Authors
  1. Noor Azilah Draman
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  2. Sabrina Ahmad
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  3. Azah Kamilah Muda
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Editor information

Editors and Affiliations

  1. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang, Malaysia

    Jasni Mohamad Zain

  2. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Kuantan, Pahang, Malaysia

    Wan Maseri bt Wan Mohd

  3. Information Systems Department, King Saud University, 11543, Riyadh, Saudi Arabia

    Eyas El-Qawasmeh

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© 2011 Springer-Verlag Berlin Heidelberg

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Draman, N.A., Ahmad, S., Muda, A.K. (2011). Recognizing Patterns of Music Signals to Songs Classification Using Modified AIS-Based Classifier. In: Zain, J.M., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22191-0_64

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  • DOI: https://doi.org/10.1007/978-3-642-22191-0_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22190-3

  • Online ISBN: 978-3-642-22191-0

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