Differential evolution schemes for speech segmentation: A comparative study
File(s)final speech ssci 2014 paper.pdf (612.15 KB)
Accepted version
Author(s)
Iliya, S
Neri, F
Menzies, D
Cornelius, P
Picinali, L
Type
Conference Paper
Abstract
This paper presents a signal processing technique for segmenting short speech utterances into unvoiced and voiced sections and identifying points where the spectrum becomes steady. The segmentation process is part of a system for deriving musculoskeletal articulation data from disordered utterances, in order to provide training feedback. The functioning of the signal processing technique has been optimized by selecting the parameters of the model. The optimization has been carried out by testing and comparing multiple Differential Evolution implementations, including a standard one, a memetic one, and a controlled randomized one. Numerical results have also been compared with a famous and efficient swarm intelligence algorithm. For the given problem, Differential Evolution schemes appear to display a very good performance as they can quickly reach a high quality solution. The binomial crossover appears, for the given problem, beneficial with respect to the exponential one. The controlled randomization appears to be the best choice in this case. The overall optimized system proved to segment well the speech utterances and efficiently detect its uninteresting parts
Date Issued
2015-01-01
Date Acceptance
2014-12-09
Citation
Proceedings of 2014 IEEE Symposium on Differential Evolution, 2015, pp.1-8
ISBN
9781479944620
Publisher
IEEE
Start Page
1
End Page
8
Journal / Book Title
Proceedings of 2014 IEEE Symposium on Differential Evolution
Copyright Statement
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
2014 IEEE Symposium on Differential Evolution (SDE)
Publication Status
Published
Start Date
2014-12-09
Finish Date
2014-12-12
Coverage Spatial
Orlando, FL USA