IDEAS home Printed from https://ideas.repec.org/a/igg/jssmet/v13y2022i1p1-28.html
   My bibliography  Save this article

The Use of Machine Learning Algorithms in the Classification of Sound: A Systematic Review

Author

Listed:
  • Akon O. Ekpezu

    (University of Ghana, Ghana)

  • Ferdinand Katsriku

    (University of Ghana, Ghana)

  • Winfred Yaokumah

    (University of Ghana, Ghana)

  • Isaac Wiafe

    (University of Ghana, Ghana)

Abstract

This study is a systematic review of literature on the classification of sounds in three domains - Bioacoustics, Biomedical acoustics, and Ecoacoustics. Specifically, 68 conferences and journal articles published between 2010 and 2019 were reviewed. The findings indicated that Support Vector Machines, Convolutional Neural Networks, Artificial Neural Networks, and statistical models were predominantly used in sound classification across the three domains. Also, the majority of studies that investigated medical acoustics focused on respiratory sounds analysis. Thus, it is suggested that studies in Biomedical acoustics should pay attention to the classification of other internal body organs to enhance diagnosis of a variety of medical conditions. With regard to Ecoacoustics, studies on extreme events such as tornadoes and earthquakes for early detection and warning systems were lacking. The review also revealed that marine and animal sound classification was dominant in Bioacoustics studies.

Suggested Citation

  • Akon O. Ekpezu & Ferdinand Katsriku & Winfred Yaokumah & Isaac Wiafe, 2022. "The Use of Machine Learning Algorithms in the Classification of Sound: A Systematic Review," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 13(1), pages 1-28, January.
  • Handle: RePEc:igg:jssmet:v:13:y:2022:i:1:p:1-28
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSSMET.298667
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Masud Ibrahim & Ssendiwal Abdallahamed & Diyawu Rahman Adam, 2018. "Service Recovery, Perceived Fairness, and Customer Satisfaction in the Telecoms Sector in Ghana," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 9(4), pages 73-89, October.
    2. Mauricio Marrone & Lutz Kolbe, 2011. "Impact of IT Service Management Frameworks on the IT Organization," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 3(1), pages 5-18, February.
    3. Neeta Baporikar & Isaac Okoth Randa, 2020. "Organizational Design for Performance Management in State-Owned Enterprises," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 11(4), pages 1-25, October.
    4. Neeti Sangwan & Vishal Bhatnagar, 2020. "Comprehensive Contemplation of Probabilistic Aspects in Intelligent Analytics," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 11(1), pages 116-141, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Florian Baer & Kurt Sandkuhl & Michael Leyer & Birger Lantow, 2021. "DESERV IT: A Method for Devolving Service Tasks in IT Services," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 419-439, August.
    2. Alimam, Mayla & Bertin, Emmanuel & Crespi, Noel, 2017. "ITIL perspective on enterprise social media," International Journal of Information Management, Elsevier, vol. 37(4), pages 317-326.
    3. Rúben Pereira & José Braga Vasconcelos & Álvaro Rocha & Isaías Scalabrin Bianchi, 2021. "Business process management heuristics in IT service management: a case study for incident management," Computational and Mathematical Organization Theory, Springer, vol. 27(3), pages 264-301, September.
    4. Rui Silva & Ana Amaro & Alvaro Dias, 2022. "Professionalism Perception and Client Satisfaction: An Analysis of the Bouncers-Doormen Performance," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 13(1), pages 1-18, January.
    5. Jalal Rajeh Hanaysha & Mohammed Emad Al-Shaikh & Shanmugan Joghee & Haitham M. Alzoubi, 2022. "Impact of Innovation Capabilities on Business Sustainability in Small and Medium Enterprises," FIIB Business Review, , vol. 11(1), pages 67-78, March.
    6. Iden, Jon & Eikebrokk, Tom Roar, 2013. "Implementing IT Service Management: A systematic literature review," International Journal of Information Management, Elsevier, vol. 33(3), pages 512-523.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jssmet:v:13:y:2022:i:1:p:1-28. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.