Abstract
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. © 2008 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Pinto, J., Sivaram, G. S. V. S., & Hermansky, H. (2008). Reverse correlation for analyzing MLP posterior features in ASR. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5246 LNAI, pp. 469–476). https://doi.org/10.1007/978-3-540-87391-4_60
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
