Automatically incorporating unknown words in JUPITER

This paper concerns the handling of out-of-vocabulary (OOV) words in the JUPITER weather information system. Specifically our objective is to deal with weather queries regarding unknown cities. We have implemented a system which can detect the presence of an unknown city name, and immediately propose a plausible spelling for that city. Potentially, the city can be dynamically incorporated into the recognizer lexicon. The three-stage system described in [1] was implemented in the JUPITER domain, and this paper will detail the development of a system that uses an ANGIE-based framework to model both spelling and pronunciation simultaneously, and uses automatically derived novel lexical units in the first stage. We report results on an independent test set containing unknown cities. Compared with a single-stage baseline, word error was reduced by 29.3% (from 24.6% to 17.4%) and understanding error was reduced by 67.5% (from 67.0% to 21.8%) on the three-stage configuration.