Title
Towards a New Image-Based Spectrogram Segmentation Speech Coder Optimised for Intelligibility
Abstract
Speech intelligibility is the very essence of communications. When high noise can degrade a speech signal to the threshold of intelligibility, for example in mobile and military applications, introducing further degradation by a speech coder could prove critical. This paper investigates concepts towards a new speech coder that draws upon the field of image processing in a new multimedia approach. The coder is based on a spectrogram segmentation image processing procedure. The design criterion is for minimal intelligibility loss in high noise, as opposed to the conventional quality criterion, and the bit rate must be reasonable. First phase intelligibility listening test results assessing its potential alongside six standard coders are reported. Experimental results show the robustness of the LD-CELP coder, and the potential of the new coder with particularly good results in car noise conditions below -4.0dB.
Year
DOI
Venue
2009
10.1007/978-3-540-92892-8_8
MMM
Keywords
Field
DocType
speech intelligibility,new image-based spectrogram segmentation,minimal intelligibility loss,speech signal,high noise,new speech coder,car noise condition,speech coder,ld-celp coder,phase intelligibility,new coder,image processing
Speech enhancement,Pattern recognition,Computer science,Spectrogram,Segmentation,Image processing,Image based,Robustness (computer science),Speech recognition,Artificial intelligence,Image compression,Intelligibility (communication)
Conference
Volume
ISSN
Citations 
5371
0302-9743
0
PageRank 
References 
Authors
0.34
14
4
Name
Order
Citations
PageRank
Keith A. Jellyman151.19
nicholas evans259454.41
W. M. Liu300.34
J. S. Mason400.68