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  •   Open Research
  • AUT Faculties
  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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An Overview of Applications and Advancements in Automatic Sound Recognition

Sharan, RV; Moir, TJ
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http://hdl.handle.net/10292/9728
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Abstract
Automatic sound recognition (ASR) has attracted increased and wide ranging interests in recent years. In this paper, we carry out a review of some important contributions in ASR techniques, mainly over the last one and a half decades. Similar to speech recognition systems, the robustness of an ASR system largely depends on the choice of feature(s) and classifier(s). We take a wider perspective in providing an overview of the features and classifiers used in ASR systems starting from early works in content-based audio classification to more recent developments in applications such as sound event recognition, audio surveillance, and environmental sound recognition. We also review techniques that have been utilized in noise robust sound recognition systems and feature optimization methods. Finally, some of the less commonly known applications of ASR are discussed.
Keywords
Automatic sound recognition; Cepstral coefficients; Deep neural networks; Sound event recognition; Support vector machines; Time–frequency image
Date
March 2016
Source
Neurocomputing, 200, 22-34.
Item Type
Journal Article
Publisher
Elsevier
DOI
10.1016/j.neucom.2016.03.020
Publisher's Version
http://www.sciencedirect.com/science/article/pii/S0925231216300406?via%3Dihub#!
Rights Statement
Copyright © 2016 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).

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