Talking vs Non-Talking: A Vision Based Approach to Detect Human Speaking Mode

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dc.contributor.authorAfroze, Sadia
dc.contributor.authorHoque, Mohammed Moshiul
dc.date.accessioned2026-07-06T21:14:23Z
dc.date.available2026-07-06T21:14:23Z
dc.date.issued7-Feb-2019
dc.description.abstractHuman talking mode detection is an important issue
dc.description.abstractin human-computer interaction. In this work, we propose a
dc.description.abstractmethod for detecting human talking and non talking mode
dc.description.abstractdetection based on supervised machine learning approach. Visual
dc.description.abstractlip information of human is considered as an important clue.
dc.description.abstractOur goal is to develop a method for human talking and non
dc.description.abstracttalking mode detection in real time using supervised classification
dc.description.abstractalgorithm. We tested our experiment with a single speaker task
dc.description.abstractand compared the results with the previous method. The results
dc.description.abstractshow that our approach can obtain a 98.00% accuracy and a
dc.description.abstractfast executed time.
dc.identifier.otherhttp://103.99.128.19:8080/jspui/handle/123456789/319
dc.identifier.urihttp://103.99.128.19:8080/xmlui/handle/123456789/319
dc.publisherFaculty of Electrical and Computer Engineering, CUET
dc.sourceCUET Digital Repository
dc.subjectComputer vision
dc.subjectfeature extraction
dc.subjectface detection
dc.subjectpattern recognition
dc.subjectevaluation
dc.titleTalking vs Non-Talking: A Vision Based Approach to Detect Human Speaking Mode
dc.title.alternativeInternational Conference on Electrical, Computer and Communication Engineering (ECCE-2019)

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