Summary form only given. The state of the art in automatic speech recognition has reached the point that searching for and extracting information from large speech repositories or streaming audio has become a growing reality. This paper summarizes the technologies that have been instrumental in making audio as searchable as text, including speech recognition, speaker clustering, segmentation, and identification; topic classification; and story segmentation. Once speech is turned into text, information extraction methods can then be applied, such as named entity extraction, finding relationships between named entities, and resolution of anaphoric references. Examples of deployed systems for information extraction from speech, which incorporate some of the aforementioned technologies, will be given.