Generalized hierarchical search in the ISIP ASR system

It has long been a goal of speech researchers to incorporate higher-level knowledge sources such as discourse, part of speech, and understanding constraints into the speech recognition problem. However, current speech recognition systems are highly tuned to N-gram, triphone-based recognition. Thus, researchers have been unable to exploit this knowledge without extensive modifications to the most complex portion of an ASR system - the decoder. In this paper we describe a publicly available, state-of-the-art decoder that employs a flexible and configurable multilevel search strategy capable of incorporating hierarchical knowledge sources with no changes to source code.