With a little help from the database-developing voice-controlled directory information systems

Automated directory information is amongst the most challenging applications of automatic speech recognition. We present some basic techniques that try to overcome the deficiencies of the speech recognizer by incorporating as much additional knowledge as possible, such as the telephone directory. We derive a maximum a-posteriori decision rule which explicitly uses the telephone directory knowledge as well as the dialogue history to improve speech understanding accuracy. The rule allows us to take a combined decision on the joint probability over multiple dialogue turns, which yields good results in combination with spelling. Our spelling architecture permits continuous spelling of names and uses a context-free grammar to parse common spelling expressions. We review two different real time prototypes, on which we evaluated our decision rule. One (PADIS) operates on a small database and one (PADIS-XL) on a database with 130000 entries