Performance of machine learning classifiers in distress keywords recognition for audio surveillance applications

The ability to recognize distress speech is the essence of an intelligent audio surveillance system. With this ability, the surveillance system can be configured to detect specific distress keywords and launch appropriate actions to prevent unwanted incidents from progressing. This paper aims to fin...

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Bibliographic Details
Main Authors: Nadhirah Johari, Mazlina Mamat, Ali Chekima
Format: Proceedings
Language:English
English
Published: Institute of Electrical and Electronics Engineers 2021
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/32526/1/Performance%20of%20machine%20learning%20classifiers%20in%20distress%20keywords%20recognition%20for%20audio%20surveillance%20applications.ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/32526/2/Performance%20of%20machine%20learning%20classifiers%20in%20distress%20keywords%20recognition%20for%20audio%20surveillance%20applications.pdf
https://eprints.ums.edu.my/id/eprint/32526/
https://ieeexplore.ieee.org/document/9573852
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