Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The Potential of Visual Features: to Improve Voice Recognition Systems in Vehicles Noisy Environment
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Multimodal biometric systems have been subject of study in recent decades, theirunique characteristic of Anti spoofing and liveness detection plus ability to deal withaudio noise made them technology candidates for improving current systems such asvoice recognition, verification and identification systems.In this work we studied feasibility of incorporating audio-visual voice recognitionsystem for dealing with audio noise in the truck cab environment. Speech recognitionsystems suffer from excessive noise from the engine and road traffic and cars stereosystem. To deal with this noise different techniques including active and passive noisecancelling have been studied.Our results showed that although audio-only systems are performing better in noisefree environment their performance drops significantly by increase in the level of noisein truck cabins, which by contrast does not affect the performance of visual features.Final fused system comprising both visual and audio cues, proved to be superior toboth audio-only and video-only systems.

Place, publisher, year, edition, pages
2014. , 49 p.
Keyword [en]
voice recognition, lip motion, optical flow
National Category
Computer Science
Identifiers
URN: urn:nbn:se:hh:diva-27273Local ID: IDE1310OAI: oai:DiVA.org:hh-27273DiVA: diva2:771771
Subject / course
Computer science and engineering
Supervisors
Examiners
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2014-12-15Bibliographically approved

Open Access in DiVA

fulltext(3730 kB)668 downloads
File information
File name FULLTEXT01.pdfFile size 3730 kBChecksum SHA-512
9989b3abf2e0614bf67227c2ba245c74928c2787ae83891f49ddedcad244aee16afaa0701eb7b9802fa831b572714e08b41c06924af0cf0482531b5b58a35694
Type fulltextMimetype application/pdf

By organisation
School of Information Science, Computer and Electrical Engineering (IDE)
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 668 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 185 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf