Talking vs Non-Talking: A Vision Based Approach to Detect Human Speaking Mode
Date
7-Feb-2019
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Faculty of Electrical and Computer Engineering, CUET
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.
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.
Description
Keywords
Computer vision, feature extraction, face detection, pattern recognition, evaluation