Accurate recognition of city names with spelling as a fall back strategy

Entering city names is an important issue for various speech driven applications such as telephone directory assistance. This paper proposes a system that combines word recognition with utterance verification and spelling as a fall back strategy. Word recognition experiments show that the use of a medium size vocabulary yields the lowest error rate when only permitting very few false acceptances. For letter recognition discriminatively trained letter models are applied. In order to shorten the spelling procedure two abort conditions are introduced which reduce the number of letters that have to be spelled. The system handles 96.5% of all calls correctly while less than 45% of all callers must spell the name.