This paper addresses the problem of building natural language

based grammars and language models for directory assistance

applications that use automatic speech recognition. As input,

one is given an electronic version of a standard phone book,

and the output is a grammar or language model that will accept

all the ways in which one might ask for a particular listing. We

focus primarily on the problem of processing listings for businesses

and government offices, but our techniques can be used

to speech-enable other kinds of large listings (like book titles,

catalog entries, etc.). We have applied these techniques to the

business listings of a state in the Midwestern United States, and

we present highly encouraging recognition results.

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In  Proceedings of Eurospeech

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