Detection of impulsive sounds in stream of audio signals
Audio 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 acoustics
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-253502023-05-29T16:08:25Z Detection of impulsive sounds in stream of audio signals Suliman A. Omarov B. Dosbayev Z. 25825739000 57202103462 57220804877 Audio 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 acoustics Video 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. Final 2023-05-29T08:08:25Z 2023-05-29T08:08:25Z 2020 Conference Paper 10.1109/ICIMU49871.2020.9243540 2-s2.0-85097640153 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097640153&doi=10.1109%2fICIMU49871.2020.9243540&partnerID=40&md5=5e629bebe8f596f067fa4da5bf7552ec https://irepository.uniten.edu.my/handle/123456789/25350 9243540 283 287 Institute of Electrical and Electronics Engineers Inc. Scopus |
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| description |
Audio 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 acoustics |
| author2 |
25825739000 |
| author_facet |
25825739000 Suliman A. Omarov B. Dosbayev Z. |
| format |
Conference Paper |
| author |
Suliman A. Omarov B. Dosbayev Z. |
| spellingShingle |
Suliman A. Omarov B. Dosbayev Z. Detection of impulsive sounds in stream of audio signals |
| author_sort |
Suliman A. |
| title |
Detection of impulsive sounds in stream of audio signals |
| title_short |
Detection of impulsive sounds in stream of audio signals |
| title_full |
Detection of impulsive sounds in stream of audio signals |
| title_fullStr |
Detection of impulsive sounds in stream of audio signals |
| title_full_unstemmed |
Detection of impulsive sounds in stream of audio signals |
| title_sort |
detection of impulsive sounds in stream of audio signals |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806423426537095168 |
| score |
13.211853 |