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...
| Main Authors: | , , |
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| Format: | Proceedings |
| Language: | English English |
| Published: |
Institute of Electrical and Electronics Engineers
2021
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| 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 |
Internet
https://eprints.ums.edu.my/id/eprint/32526/1/Performance%20of%20machine%20learning%20classifiers%20in%20distress%20keywords%20recognition%20for%20audio%20surveillance%20applications.ABSTRACT.pdfhttps://eprints.ums.edu.my/id/eprint/32526/2/Performance%20of%20machine%20learning%20classifiers%20in%20distress%20keywords%20recognition%20for%20audio%20surveillance%20applications.pdf