This paper describes a novel recursive transition network (RTN) speech decoder designed for robust processing of spontaneous spoken input. The system uses both stochastic and rule-based methods to constrain the recognition search. It is based on the multi-pass search used by the Sphinx-II speech decoder developed at Carnegie Mellon. We describe the basic decoder and system architectures and compare the system to our current loosely coupled system on spontaneous spoken dialogs from the DARPA air travel (ATIS) task. >
['Wayne H. Ward', 'Sunil Issar']
Integrating semantic constraints into the Sphinx-II recognition search