In this paper we address the problem of extracting caller information from voicemail messages, such as the identity and phone number of the caller. Previous work in information extraction from speech includes spoken document retrieval and named entity detection. This task differs from the named entity task in that the information we are interested in is a subset of the named entities in the message, and consequently, the need to pick the correct subset makes the problem more difficult. Also, the caller’s identity may include information that is not typically associated with a named entity. In this work, we present two information extraction methods, one based on hand-crafted rules, one based on statistically trained maximum entropy model.We evaluate their performance on both manually transcribed messages and on the output of a speech recognition system.