Transform-based indexing of audio data for multimedia databases

Since the relative proportion of multimedia (video, image and audio) data within databases is expected to increase substantially in the future, keyword-based indexing would be inadequate and efficient content-based query and retrieval are required. The problem of devising content based query, indexing, and retrieval for these newer data types remains an open and challenging problem. While considerable attention has recently been given to image (and, to some extent, video) indexing, much less has been devoted to the problem of indexing its unidimensional counterpart-audio data. The paper proposes content-based indexing schemes for audio data in multimedia databases. The methods are based on transform techniques used in signal processing which transform data from time (or spatial) domain to frequency domain. This offers many advantages such as easy removal of noise, efficient compression and different types of processing. Two algorithms for indexing are presented along with experimental results.