ISADORA - a Speech Modelling Network Based on Hidden Markov Models (1993)
| Venue: | on Hidden Markov Models. Computer Speech & Language |
BibTeX
@INPROCEEDINGS{Schukat-talamazzini93isadora-,
author = {E. G. Schukat-talamazzini and H. Niemann},
title = {ISADORA - a Speech Modelling Network Based on Hidden Markov Models},
booktitle = {on Hidden Markov Models. Computer Speech & Language},
year = {1993},
pages = {page}
}
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Abstract
In this paper we present the ISADORA system which provides highly flexible speech recognition based on HMM technology together with an hierarchical representation of speech units. Markov model topologies, subword unit inventories, regular grammars expressed in finite-state or phrase structure style, and even the analysis tasks themselves are explicitly represented by the nodes of a large speech unit network. Thus, nothing that can be "said in the language of Markov models" needs to be hard-wired in the program code. In contrast to traditional compiled network recognizers, units, grammars, and tasks may be created or modified at analysis time, and the outcome of the decoding process is a structured symbolic description of the sensory input. Our architecture has proven extremely useful in prototyping new kinds of subword units. Besides generalized triphones and context-freezing units, a new subword speech unit for automatic speech recognition has been implemented. The so-called polyphone...
