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Bioinspired Auditory Sound Localisation for Improving the Signal to Noise Ratio of Socially Interactive Robots

John C. Murray, Stefan Wermter, Harry R. Erwin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we describe a bioinspired hybrid architecture for acoustic sound source localisation and tracking to increase the signal to noise ratio (SNR) between speaker and background sources for a socially interactive robot's speech recogniser system. The model presented incorporates the use of Interaural Time Difference for azimuth estimation and Recurrent Neural Networks for trajectory prediction. The results are then presented showing the difference in the SNR of a localised and non-localised speaker source, in addition to presenting the recognition rates between a localised and non-localised speaker source. From the results presented in this paper it can be seen that by orientating towards the sound source of interest the recognition rates of that source can be increased.

Original languageEnglish
Title of host publication2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
PublisherIEEE
Pages1206-1211
Number of pages6
ISBN (Electronic)142440259X
ISBN (Print)1424402581
DOIs
Publication statusPublished - 15 Jan 2007
Externally publishedYes
Event2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 - Beijing, China
Duration: 9 Oct 200615 Oct 2006

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
PublisherIEEE
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Country/TerritoryChina
CityBeijing
Period9/10/0615/10/06

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