Multichannel filters for speech recognition using a particle swarm optimization

Kit Yan Chan, Sven Nordholm, Ka Fai Cedric Yiu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Speech recognition has been used in various real-world applications such as automotive control, electronic toys, electronic appliances etc. In many applications involved speech control functions, a commercial speech recognizer is used to identify the speech commands voiced out by the users and the recognized command is used to perform appropriate operations. However, users' commands are often corrupted by surrounding ambient noise. It decreases the effectiveness of speech recognition in order to implement the commands accurately. This paper proposes a multichannel filter to enhance noisy speech commands, in order to improve accuracy of commercial speech recognizers which work under noisy environment. An innovative particle swarm optimization (PSO) is proposed to optimize the parameters of the multichannel filter which intends to improve accuracy of the commercial speech recognizer working under noisy environment. The effectiveness of the multichannel filter was evaluated by interacting with a commercial speech recognizer, which was worked in a warehouse.
Original languageEnglish
Title of host publication2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012
Pages937-942
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012 - Guangzhou, China
Duration: 5 Dec 20127 Dec 2012

Conference

Conference2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012
Country/TerritoryChina
CityGuangzhou
Period5/12/127/12/12

Keywords

  • multi-channel filter
  • speech enhancement
  • Speech recognition
  • swarm optimization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering

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