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.