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Exploring current research trends in sound event detection: a systematic literature review

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Abstract

Sound Event Detection (SED) plays a significant role in the present research, implemented in several areas such as Computer Science, Healthcare, Environmental Science, Security and Surveillance, etc. With the advancement of technology, SED can be deployed to mimic the human auditory system. In this paper, we have undertaken a Systematic Literature Review focused on sound event detection, presenting a comprehensive and well-structured analysis and in-depth discussions. This review is based on the authors' extensive knowledge and expertise in the field, and it compares various algorithms employed for sound event detection. The primary objective of this study is to offer valuable insights into datasets, feature extraction techniques, and execution models commonly used in SED, along with an examination of their corresponding accuracy, challenges, and limitations. Furthermore, the paper delves into identifying potential trends within the field, offering forward-looking information that can be invaluable for future research and development efforts in sound event detection. This systematic review aims to contribute to the continued advancement of SED technologies and applications by synthesizing existing knowledge and identifying emerging directions. It provides a foundation for researchers, practitioners, and stakeholders to make informed decisions and explore new possibilities within this evolving domain.

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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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  1. School of Computer Science and Artificial Intelligence, SR University, Warangal, Telangana, India

    Sallauddin Mohmmad

  2. Research Scholar, JNTU, Hyderabad, India

    Sallauddin Mohmmad

  3. Department of Information Technology, JNTUH College of Engineering, Nachupally, Kondagattu, Jagtial, Telangana, India

    Suresh Kumar Sanampudi

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Mohmmad, S., Sanampudi, S.K. Exploring current research trends in sound event detection: a systematic literature review. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18740-9

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  • DOI: https://doi.org/10.1007/s11042-024-18740-9

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