The phenomenal increase in the amounts of audio (and multimedia) data being generated, processed, and used in several computer applications have necessitated the development of audio (and multimedia) database systems with newer features such as content-based queries and similarity searches to manage and use such data. Example applications of audio databases are in digital libraries, entertainment industry, forensic laboratories and virtual reality, among others. Fast and accurate retrieval for content-based queries are crucial for such systems to be useful. Efficient content-based indexing and similarity searching schemes are keys to providing fast and relevant data retrieval. This paper presents a scheme for indexing of audio data based on wavelets. The performance of this scheme has been experimentally evaluated and is seen to be more resilient to noise than the indexing schemes using signal-level statistics, and give better retrieval precision than DCT-based indexing.
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