Comparison of HMM experts with MLP experts in the Full Combination Multi-Band Approach to Robust ASR
| Type of publication: | Idiap-RR |
| Citation: | astrid-00-21a |
| Number: | Idiap-RR-21-2000 |
| Year: | 2000 |
| Month: | 7 |
| Institution: | IDIAP |
| Address: | Martigny, Switzerland |
| Note: | Published: ICSLP 2000, Beijing, September 2000 |
| Abstract: | In this paper we apply the Full Combination (FC) multi-band approach, which has originally been introduced in the framework of posterior-based HMM/ANN (Hidden Markov Model/Artificial Neural Network) hybrid systems, to systems in which the ANN (or Multilayer Perceptron (MLP)) is itself replaced by a Multi Gaussian HMM (MGM). Both systems represent the most widely used statistical models for robust ASR (automatic speech recognition). It is shown how the FC formula for the likelihood-based MGMs can easily be derived from the posterior-based approach by simply applying Bayes' Rule. The experiments show that the Full Combination multi-band system with MGM experts performs better, in all noise conditions tested, than the simple sum and product rules which are normally used. As compared to the baseline full-band system, the FC system shows increased robustness mainly on band-limited noise. The goal of this article is not a performance comparison between Multilayer Perceptrons and Multi Gaussian Models but between the theory of the two approaches, posterior-based vs. likelihood-based FC approach, so results are only given for the MGMs. |
| Userfields: | ipdinar={2000}, ipdmembership={speech}, language={English}, |
| Keywords: | full combination, HMM/ANN-Hybrid, multi-band, multi-stream |
| Projects |
Idiap |
| Authors | |
| Crossref by |
astrid-00-21b |
| Added by: | [UNK] |
| Total mark: | 0 |
|
Attachments
|
|
|
|
|
Notes
|
|
|
|
|
