Estimation of Global Posteriors and Forward-Backward Training of Hybrid HMM/ANN Systems
| Type of publication: | Inproceedings |
| Citation: | henn97:euro |
| Booktitle: | European Conference on Speech Communication and Technology (EUROSPEECH 97), Rhodes, Greece |
| Year: | 1997 |
| Pages: | 1951-1954 |
| URL: | http://diuf.unifr.ch/people/he... |
| Abstract: | The results of our research presented in this paper is two-fold. First, an estimation of global posteriors is formalized in the framework of hybrid HMM/ANN systems. It is shown that hybrid HMM/ANN systems, in which the ANN part estimates local posteriors, can be used to modelize global model posteriors. This formalization provides us with a clear theory in which both REMAP and ``classical'' Viterbi trained hybrid systems are unified. Second, a new forward-backward training of hybrid HMM/ANN systems is derived from the previous formulation. Comparisons of performance between Viterbi and forward-backward hybrid systems are presented and discussed. |
| Keywords: | ANN, MLP, Speech Recognition |
| Authors | |
| Added by: | [] |
| Total mark: | 0 |
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