logo Idiap Research Institute        
 [BibTeX] [Marc21]
Volterra Series for Analyzing MLP based Phoneme Posterior Probability Estimator
Type of publication: Idiap-RR
Citation: Pinto_Idiap-RR-69-2008
Number: Idiap-RR-69-2008
Year: 2008
Month: 10
Institution: Idiap
Abstract: We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. The identified Volterra kernels reveal the spectro-temporal patterns that are learned by the trained system for each phoneme. To demonstrate the applicability of Volterra series, we analyze a multilayered perceptron trained using Mel filter bank energy features and analyze its first order Volterra kernels.
Keywords:
Projects SNSF-KEYSPOT
IM2
SNSF-MULTI
Authors Pinto, Joel Praveen
Sivaram, G. S. V. S.
Hermansky, Hynek
Magimai.-Doss, Mathew
Crossref by Pinto_ICASSP_2009
Added by: [ADM]
Total mark: 0
Attachments
  • Pinto_Idiap-RR-69-2008.pdf (MD5: 6530fd83bd7366a2635ce48ffebd9002)
Notes