Audio Content Description in Sound Databases

Sound database indexing requires metadata to represent audio content of the data. If the metadata are not attached to the database by its creator, content information has to be extracted directly from sounds, using descriptors based on sound analysis. In this paper, authors present a number of sound descriptors based on various forms of signal analysis. Telescope Vector trees (TV-trees) and Frame Segment trees (FS-trees) are applied to represent audio content on the basis of the extracted sound descriptors and metadata provided by the database creator (if only available). Such a representation of audio content of the database is used to speed up the search of the audio material in multimedia databases.