Continued development of an IMELDA based voice recognition system for persons with severe disabilities

Authors

  • G.E. Birch Neil Squire Found., North Vancouver, BC, Canada
  • D.A. Zwierzynski
  • C. Lefebvre
  • D. Starks

Keywords:

handicapped aids, speech recognition equipment, speech recognition system, front-end component, back-end component, dynamic programming, mel-scale fast-fourier-transform based spectral filter-bank analysis, linear transformation, IMELDA, linear discriminant analysis

Abstract

The general design of the authors' speech recognition system is such that the acoustic features are first extracted from the speech signal in the front-end component. Subsequently, these features are passed on to the back-end component where they are compared with stored templates through the technique of dynamic programming. The front-end processing in their speech recognition system is a mel-scale fast-fourier-transform based spectral filter-bank analysis followed by a linear transformation. This linear transformation, which is called IMELDA, was developed and tested and is based on linear discriminant analysis. Comparisons with other systems indicate that it is the `state of the art' for front-end processing in a robust speech recognition system, outperforming other transforms and recognition systems, particularly in degraded speech

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Published

1992-09-01

How to Cite

1.
Birch G, Zwierzynski D, Lefebvre C, Starks D. Continued development of an IMELDA based voice recognition system for persons with severe disabilities. Canadian Acoustics [Internet]. 1992 Sep. 1 [cited 2021 Oct. 20];20(3):45-6. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/728

Issue

Section

Proceedings of the Acoustics Week in Canada