A generic classification system for multi-channel audio indexing: Application to speech and music detection

Benaroya, Elie-Laurent; Peeters, Geoffroy

doi:10.1109/wiamis.2013.6616160

Cited by 2 publications

(1 citation statement)

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“…Finally, sound requires lesser computational resources as compared to an image or video [3], [4]. Thus, a SED system has great potential in many other domains besides speech recognition [5], [6] such as medical telemonitoring [7], surveillance [8], [9], equipment monitoring [10] [11] and wildlife monitoring [12], [13].…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Polyphonic Sound Event Detection

Chan

Chin

2020

IEEE Access

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One of the most amazing functions of the human auditory system is the ability to detect all kinds of sound events in the environment. With the technologies and hardware advances, polyphonic Sound Event Detection (SED) can be developed to mimic the ability of the human auditory system. However, the development of a SED system is no trivial task, and several different factors often hinder accuracy. Although there are several overview papers available, most of them only provide a theoretical overview of algorithms used with little discussion. Thus, to the best of the authors' knowledge, there is no comprehensive review that covers this particular domain. Therefore, this paper aims to provide an in-depth discussion of different methodologies proposed by various authors that include the features used, detection algorithms, and their corresponding accuracy and limitations. Additional information on possible trends is also discussed that can be useful for future development works.

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