Automatic Acquisition of Names Using Speak and Spell Mode in Spoken Dialogue Systems

This paper describes a novel multi-stage recognition procedure for deducing the spelling and pronunciation of an open set of names. The overall goal is the automatic acquisition of unknown words in a human computer conversational system. The names are spoken and spelled in a single utterance, achieving a concise and natural dialogue flow. The first recognition pass extracts letter hypotheses from the spelled part of the waveform and maps them to phonemic hypotheses via a hierarchical sublexical model capable of generating graphemephoneme mappings. A second recognition pass determines the name by combining information from the spoken and spelled part of the waveform, augmented with language model constraints. The procedure is integrated into a spoken dialogue system where users are asked to enroll their names for the first time. The acquisition process is implemented in multiple parallel threads for real-time operation. Subsequent to inducing the spelling and pronunciation of a new name, a series of operations automatically updates the recognition and natural language systems to immediately accommodate the new word. Experiments show promising results for letter and phoneme accuracies on a preliminary dataset. The research at CNRI was supported by DARPA under contract number N66001-00-2-8922, monitored through SPAWAR Systems Center, San Diego. The research at MIT was supported by DARPA under contract number NBCH1020002 monitored through the Dept. of the Interior, National Business Center, Acquisition Services Div., Fort Huachuca, AZ.