DocumentCode
2705183
Title
Combination of Acoustic Classifiers Based on Dempster-Shafer Theory of Evidence
Author
Valente, Fabio ; Hermansky, Hynek
Author_Institution
IDIAP Res. Inst.
Volume
4
fYear
2007
fDate
15-20 April 2007
Abstract
In this paper we investigate combination of neural net based classifiers using Dempster-Shafer theory of evidence. Under some assumptions, combination rule resembles a product of errors rule observed in human speech perception. Different combination are tested in ASR experiments both in matched and mismatched conditions and compared with more conventional probability combination rules. Proposed techniques are particularly effective in mismatched conditions.
Keywords
speech processing; speech recognition; acoustic classifiers; automatic speech recognition; evidence Dempster-Shafer theory; human speech perception; neural net based classifiers; Atomic measurements; Automatic speech recognition; Bayesian methods; Humans; Multilayer perceptrons; Neural networks; Speech recognition; Testing; Classifier combination; Dempster-Shafer theory; Multi-Stream ASR;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location
Honolulu, HI
ISSN
1520-6149
Print_ISBN
1-4244-0727-3
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2007.367273
Filename
4218304
Link To Document