We are interested in providing automated services via natural spoken dialog systems. By natural, we mean that the machine understands and acts upon what people actually say, in contrast to what one would Like them to say. There are many issues that arise when such systems are targeted for large populations of non-expert users. In this paper, we focus on the task of automatically routing telephone calls based on a user's fluently spoken response to the open-ended prompt of "How may I help you?". We first describe a database generated from 10,000 spoken transactions between customers and human agents. We then describe methods for automatically acquiring language models for both recognition and understanding from such data. Experimental results evaluating call-classification from speech are reported for that database. These methods have been embedded within a spoken dialog system, with subsequent processing for information retrieval and formfilling. (C) 1997 Elsevier Science B.V.