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2021 | OriginalPaper | Buchkapitel

Audio Surveillance: Detection of Audio-Based Emergency Situations

verfasst von : Zhandos Dosbayev, Rustam Abdrakhmanov, Oxana Akhmetova, Marat Nurtas, Zhalgasbek Iztayev, Lyazzat Zhaidakbaeva, Lazzat Shaimerdenova

Erschienen in: Advances in Computational Collective Intelligence

Verlag: Springer International Publishing

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Abstract

The subject of the study was the recognition of sounds of critical situations in the audio signal. The term “critical situation” is understood as an event, the characteristic sound signs of which can speak about acoustic artifacts as a shot, a scream, a glass crash, an explosion, a siren, etc.. The paper considers the scope of audio analytics, its advantages, the history of spectral analysis, as well as analyzes and selects tools for further development of system components. In the paper, we propose our dataset that consists of 14 classes that contains 1000 sounds of each, and a model to detect emergency situations using audio processing and analytics.

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Titel: Audio Surveillance: Detection of Audio-Based Emergency Situations
verfasst von: Zhandos Dosbayev
Rustam Abdrakhmanov
Oxana Akhmetova
Marat Nurtas
Zhalgasbek Iztayev
Lyazzat Zhaidakbaeva
Lazzat Shaimerdenova
Verlag: Springer International Publishing
Buch: Advances in Computational Collective Intelligence
Print ISBN: 978-3-030-88112-2

Electronic ISBN: 978-3-030-88113-9

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-88113-9_33

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