By Topic

Sound source recognition for human robot interaction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Yaozhang Pan ; Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore ; Ge, S.S. ; Al Mamun, A. ; Brekke, E.

A very important aspect in developing human-robot interaction (HRI) is the ability to recognize people by sound source recognition. In this paper, we introduce an intelligent audio human detection system that is able to recognize userpsilas voice, and identified it from background sound. The sound sources recognition for human robot interaction is investigated using an unsupervised learning algorithm, neighborhood linear embedding (NLE), which is able to extract the intrinsic features such as neighborhood relationships, global distributions and clustering property of a given data set. Furthermore, motivated by the scale adaptivity of humanpsilas perception, several scale invariant metrics are designed to enhance the intrinsic feature extraction performance of NLE. Simulations on different sound sources recognition are studied to demonstrate effective applications of the scale invariant NLE algorithm for robust sound recognition and identification to improve auditory system of robot for human robot interaction.

Published in:

Robot and Human Interactive Communication, 2008. RO-MAN 2008. The 17th IEEE International Symposium on

Date of Conference:

1-3 Aug. 2008