Low-cost hardware speech enhancement for improved speech recognition in automotive environments
Whittington, J., Ye, H., Kamalakannan, K., Vu, N.V., Mason, M.W., Kleinschmidt, T., & Sridharan, S. (2010) Low-cost hardware speech enhancement for improved speech recognition in automotive environments. In Doyle, Neil (Ed.) 24th ARRB Conference Proceedings, ARRB Group Ltd., Australia, Victoria, Melbourne, pp. 1-17.
Voice recognition is one of the key enablers to reduce driver distraction as in-vehicle systems become more and more complex. With the integration of voice recognition in vehicles, safety and usability are improved as the driver’s eyes and hands are not required to operate system controls. Whilst speaker independent voice recognition is well developed, performance in high noise environments (e.g. vehicles) is still limited. La Trobe University and Queensland University of Technology have developed a low-cost hardware-based speech enhancement system for
automotive environments based on spectral subtraction and delay–sum beamforming techniques. The enhancement algorithms have been optimised using authentic Australian
English collected under typical driving conditions. Performance tests conducted using speech data collected under variety of vehicle noise conditions demonstrate a word recognition rate improvement in the order of 10% or more under the noisiest conditions. Currently developed to
a proof of concept stage there is potential for even greater performance improvement.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||FPGA, Speech Enhancement, Speech Recognition, Automotive Environment|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Microelectronics and Integrated Circuits (090604)|
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
Past > Institutes > Information Security Institute
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2010 ARRB Group Ltd and please consult the authors.|
|Deposited On:||09 Nov 2010 12:12|
|Last Modified:||01 Mar 2012 00:31|
Repository Staff Only: item control page