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

Afroze, Sadia; Hoque, Mohammed Moshiul

dc.contributor.author	Afroze, Sadia
dc.contributor.author	Hoque, Mohammed Moshiul
dc.date.accessioned	2021-10-25T05:59:00Z
dc.date.available	2021-10-25T05:59:00Z
dc.date.issued	2019-02-07
dc.identifier.isbn	978-1-5386-9111-3
dc.identifier.uri	http://103.99.128.19:8080/xmlui/handle/123456789/319
dc.description.abstract	Human 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.iso	en_US	en_US
dc.publisher	Faculty of Electrical and Computer Engineering, CUET	en_US
dc.relation.ispartofseries	ECCE;
dc.subject	Computer vision	en_US
dc.subject	feature extraction	en_US
dc.subject	face detection	en_US
dc.subject	pattern recognition	en_US
dc.subject	evaluation	en_US
dc.title	Talking vs Non-Talking: A Vision Based Approach to Detect Human Speaking Mode	en_US
dc.title.alternative	International Conference on Electrical, Computer and Communication Engineering (ECCE-2019)	en_US
dc.type	Article	en_US