A major impediment when using video material such as television news broadcasts and other visual documentation footage is the difficulty to search for appropriate material in video databases comprising easily hundreds of hours of material. Although the material is available in electronic format, it cannot effectively be searched. Manual search is a time-consuming and expensive option. Reliable techniques for converting audio data in a standard textual form already exist.
Every recording consists of approx.
15 minutes of data is then segmented into shorter pieces by their acoustic properties only. The recognizer's output, the so-called hypotheses, are automatically entered into a database together with the original audio and video material shortly after the broadcast. Also, the hypotheses can be labeled with a measure of confidence we developed and used for further training of the speech recognizer without the need for manually generated transcripts, a time-consuming and therefore expensive process. User queries can be entered via a web-based interface and by speech input. The system's response is a list of the found segments, sorted according to their relevance, along with a thumbnail picture of the segment and the day of the broadcast.