Combining syntactical and statistical language constraints in context-dependent language models for interactive speech applications.

In interactive speech applications the expected vocabulary and the expected user utterances change from one dialogue step to the next one. The use of several context dependent language models results in a better system performance than the use of a single model. In this paper we present a new approach combining syntactical and statistical language constraints to a single language model. Recognition results on a database of spelled city names are presented. Furthermore a match against the list of all possible city names is performed.