An Agent-based Framework for Speech Investigation

This paper presents a novel agent-based framework for investigating
speech recognition which combines statistical data
and explicit phonological knowledge in order to explore strategies
aimed at augmenting the performance of automatic speech
recognition (ASR) systems. This line of research is motivated
by a desire to provide solutions to some of the more notable
problems encountered, including in particular the problematic
phenomena of coarticulation, underspecified input, and out-ofvocabulary
items. This research also seeks to promote the use
of deliberative reasoning agents in the speech and natural language
processing arenas.