The quantity of audio data produced in the world is truly vast. Audio, as a medium, is regarded as a second-class citizen to text. While most of the current emphasis on searching, summarization, and indexing is focused primarily on text, more original language content is being generated through the audio portion of video and dedicated audio media such as radio and telephone than in text alone. One obvious way to tackle this problem is to transcribe the speech-based audio using automatic speech recognition technology. Recent advances in speech recognition and natural language technologies make it possible to turn a previously opaque form of data - audio, in the form of speech - into a searchable, indexable, manipulable form. We will describe a system that uses speech recognition along with several natural language technologies to give a user the ability to search, browse, and classify a large database of spoken audio, show how such a system can be used, and describe further problems and potential research areas in the field of audio indexing.