In this article we present DANCERS, a system for automated indexing and retrieval of TV broadcast news. The system output, a topic-based report organization structure, is obtained in three major steps. In the first step, the visual and the speech streams of a news program are analyzed in order to partition the program into report segments. In the second step, the transcribed speech of each of the report segments is matched with the content of a large prespecified textual topic database. This database covers a large number of topics and can be updated anytime, e.g., according to the user’s interests. The result of the matching procedure is a list of most probable topics per report segment that are used in the last step to merge related neighboring segments into reports. The most probable topics that serve as the base for the segmentmerging procedure are at the same time the indexes of the newly created reports, using which the reports can be retrieved or classified. A relative simplicity of the indexing approach, minimized user involvement and highly satisfying indexing performance are the major characteristics of our system.