DocumentCode :
3307397
Title :
The methods of pathological speech visualization [using Kohonen neural networks]
Author :
Tadeusiewicz, R. ; Wszolek, W. ; Izworski, Antoni ; Wszolek, T.
Author_Institution :
Dept. of Autom., Univ. of Min. & Metall., Krakow, Poland
Volume :
2
fYear :
1999
fDate :
36434
Abstract :
In tasks related to the analysis and recognition of pathological speech it is often more important to provide the respective person (e.g. physician) with guidelines for a qualitative evaluation of this speech than to achieve a very accurate automated recognition. By ear it is easy to judge whether the speech is regular or deformed, but any attempt of a quantitative evaluation is not satisfactory. If the speech is transformed to a graphic form, by a proper visualization method, it is easier for a person to estimate its deformation degree by comparing the respective graphical patterns. The new visualization method proposed is based on the results obtained by application of Kohonen neural networks
Keywords :
medical signal processing; pattern classification; self-organising feature maps; signal classification; speech processing; speech recognition; Kohonen neural networks; articulation; graphical patterns; pathological speech visualization; qualitative evaluation; signal registration multi-spectrum; speech analysis; speech recognition; winner neurons; Automatic speech recognition; Data visualization; Ear; Gold; Neural networks; Pathology; Signal processing; Speech analysis; Speech processing; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
ISSN :
1094-687X
Print_ISBN :
0-7803-5674-8
Type :
conf
DOI :
10.1109/IEMBS.1999.804134
Filename :
804134
Link To Document :
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