Publication:
Detection of impulsive sounds in stream of audio signals

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dc.citedby4
dc.contributor.authorSuliman A.en_US
dc.contributor.authorOmarov B.en_US
dc.contributor.authorDosbayev Z.en_US
dc.contributor.authorid25825739000en_US
dc.contributor.authorid57202103462en_US
dc.contributor.authorid57220804877en_US
dc.date.accessioned2023-05-29T08:08:25Z
dc.date.available2023-05-29T08:08:25Z
dc.date.issued2020
dc.descriptionAudio systems; Data streams; Security systems; Signaling; Support vector machines; Video cameras; Video recording; Analytics systems; Automatic Detection; Computing power; Impulsive sounds; Maintenance cost; Security cameras; Urban surveillance; Video analytics; Audio acousticsen_US
dc.description.abstractVideo analysis has become a standard feature of many security cameras. However, built-in audio analytics continues to be quite rare despite the presence of both the audio channel itself in the devices and the available computing power for processing audio data. Audio analytics has some advantages over video analytics such as cheaper devices and maintenance costs. Furthermore, when the system is running in real-time, the audio data stream is significantly smaller in volume than the data stream from video cameras and makes it more loyal requirements for the bandwidth of the data channel. Audio analytics systems can be particularly useful for urban surveillance with the start of automated broadcasting live video to the police console from the scene of an explosion and shooting. Audio analytics technologies can also be used to study video recordings and determine events. This article proposes a method for automatic detection of pulse sounds that signifies critical situation in audio signals based on Support Vector Machine learning models. The models were able to classify sounds from events such as gunshot, broken glass, explosion, siren, cry and dog barking with accuracy ranges from 95% to 81 %. � 2020 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9243540
dc.identifier.doi10.1109/ICIMU49871.2020.9243540
dc.identifier.epage287
dc.identifier.scopus2-s2.0-85097640153
dc.identifier.spage283
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097640153&doi=10.1109%2fICIMU49871.2020.9243540&partnerID=40&md5=5e629bebe8f596f067fa4da5bf7552ec
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25350
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2020 8th International Conference on Information Technology and Multimedia, ICIMU 2020
dc.titleDetection of impulsive sounds in stream of audio signalsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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