Volterra Series for Analyzing MLP based Phoneme Posterior Probability Estimator
| Type of publication: | Conference paper |
| Citation: | Pinto_ICASSP_2009 |
| Booktitle: | Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| Year: | 2009 |
| Crossref: | Pinto_Idiap-RR-69-2008: |
| 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: |
Idiap SNSF-KEYSPOT SNSF-MULTI IM2 |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
|
Attachments
|
|
|
|
|
Notes
|
|
|
|
|
