Reverse Correlation for Analyzing MLP Posterior Features in ASR

In this work, we investigate the reverse correlation technique for analyzing posterior feature extraction using an multilayered perceptron trained on multi-resolution RASTA (MRASTA) features. The filter bank in MRASTA feature extraction is motivated by human auditory modeling. The MLP is trained bas...

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Bibliographic Details
Published inText, Speech and Dialogue pp. 469 - 476
Main Authors Pinto, Joel, Sivaram, Garimella S. V. S., Hermansky, Hynek
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Critical Band
Gaussian Mixture Model
Human Auditory System
Reverse Correlation
Stimulus Space
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Summary:In this work, we investigate the reverse correlation technique for analyzing posterior feature extraction using an multilayered perceptron trained on multi-resolution RASTA (MRASTA) features. The filter bank in MRASTA feature extraction is motivated by human auditory modeling. The MLP is trained based on an error criterion and is purely data driven. In this work, we analyze the functionality of the combined system using reverse correlation analysis.
ISBN:9783540873907
3540873902
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-87391-4_60