Abstract
An earlier work of the authors introduced an adapted version of the Computational Geometry Algorithm (CGA) designed to analyse an audio stream and produce a unique coding-independent fingerprint. As the adaptability and the induced calculation load of the proposed algorithm form a key characteristic for multiple applications, our current investigation aims to measure its performance and stability in dynamic, real-time applications, i.e., in large audio library indexing and dynamic audio recognition. In addition, we investigate the fact that context similarity is also evident across fingerprints; hence a number of comparisons are used to explore the possible uses of this highly desirable algorithmic feature.
Highlights
The wide availability of Internet connectivity and media-enabled devices has altered the way content is produced, distributed and reproduced
We evaluated the proposed audio fingerprinting and classification algorithm efficiency under three different, but typical and widely-employed application scenarios: a) the compressed application scenario, which aims to assess the identification efficiency of the Computational Geometry Algorithm (CGA) algorithm for compressed quality audio
C) the different performance scenario, were we aim at investigating the identification capabilities of the CGA algorithm on the same audio/music material, performed under different conditions
Summary
The wide availability of Internet connectivity and media-enabled devices has altered the way content is produced, distributed and reproduced. These global changes introduce new markets and services (Simpson, 2004), a fact that is clearly evident when observing the evolution of standards such as MPEG-7 linking content to context and offering multimedia accessibility for all as with MPEG-21 (Kosch, 2004). Audio (and/or video streams) are often degraded in terms of quality due to the employment of various compression techniques and the inevitable stream re-compression processes introduced by the wide variety of transmission formats available in all media-enabled platforms These algorithmic-based compression processes such as MPEG 1, 2, 3 and 4 are based on mechanisms of human perception for minimizing the required transmission bandwidth.
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