Please use this identifier to cite or link to this item: http://103.99.128.19:8080/xmlui/handle/123456789/319
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dc.contributor.authorAfroze, Sadia-
dc.contributor.authorHoque, Mohammed Moshiul-
dc.date.accessioned2021-10-25T05:59:00Z-
dc.date.available2021-10-25T05:59:00Z-
dc.date.issued2019-02-07-
dc.identifier.isbn978-1-5386-9111-3-
dc.identifier.urihttp://103.99.128.19:8080/xmlui/handle/123456789/319-
dc.description.abstractHuman talking mode detection is an important issue in human-computer interaction. In this work, we propose a method for detecting human talking and non talking mode detection based on supervised machine learning approach. Visual lip information of human is considered as an important clue. Our goal is to develop a method for human talking and non talking mode detection in real time using supervised classification algorithm. We tested our experiment with a single speaker task and compared the results with the previous method. The results show that our approach can obtain a 98.00% accuracy and a fast executed time.en_US
dc.language.isoen_USen_US
dc.publisherFaculty of Electrical and Computer Engineering, CUETen_US
dc.relation.ispartofseriesECCE;-
dc.subjectComputer visionen_US
dc.subjectfeature extractionen_US
dc.subjectface detectionen_US
dc.subjectpattern recognitionen_US
dc.subjectevaluationen_US
dc.titleTalking vs Non-Talking: A Vision Based Approach to Detect Human Speaking Modeen_US
dc.title.alternativeInternational Conference on Electrical, Computer and Communication Engineering (ECCE-2019)en_US
dc.typeArticleen_US
Appears in Collections:proceedings in CSE

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