Task modelling by sentence templates

Speech recognition applications always face the problem of changing vocabulary and functionality. The use of speech recognition systems will become more attractive if the system user is able to define or redefine the task himself in a suitable manner. Modelling a new task normally requires the experience of a human expert and a lot of time. Aditionally, the expert always has to be contacted if system changes become necessary. In this paper we present a fully operational system for continuous speech recognition with a powerful user interface. Most of the internal aspects of the speech recognition system are hidden. The task may be divided into different subtasks corresponding to dialogue states. Each subtask is defined by a set of expected user utterances based on sentence templates. This definition is automatically transformed into a lexicon and a language model used by the speech recognition system.