MAC, a system for automatically IPR identification, collection and distribution

Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.info:eu-repo/semantics/acceptedVersio

A Geometric Approach to Pattern Matching in Polyphonic Music

The music pattern matching problem involves finding matches of a small fragment of music called the "pattern" into a larger body of music called the "score". We represent music as a series of horizontal line segments in the plane, and reformulate the problem as finding the best translation of a small set of horizontal line segments into a larger set of horizontal line segments. We present an efficient algorithm that can handle general weight models that measure the musical quality of a match of the pattern into the score, allowing for approximate pattern matching. We give an algorithm with running time O(nm(d + log m)), where n is the size of the score, m is the size of the pattern, and d is the size of the discrete set of musical pitches used. Our algorithm compares favourably to previous approaches to the music pattern matching problem. We also demonstrate that this geometric formulation of the music pattern matching problem is unlikely to have a significantly faster algorithm since it is at least as hard as 3SUM, a basic problem that is conjectured to have no subquadratic algorithm. Lastly, we present experiments to show how our algorithm can find musically sensible variations of a theme, as well as polyphonic musical patterns in a polyphonic score

Stochastic model of a robust audio fingerprinting system

An audio fingerprint is a compact representation of the perceptually relevant parts of audio content. A suitable audio fingerprint can be used to identify audio files, even if they are severely degraded due to compression or other types of signal processing operations. When degraded, the fingerprint closely resembles the fingerprint of the original, but is not identical. We plan to use a fingerprint not only to identify the song but also to assess the perceptual quality of the compressed content. In order to develop such a fingerprinting scheme, a model is needed to assess the behavior of a fingerprint subject to compression. In this paper we present the initial outlines of a model for an existing robust fingerprinting system to develop a more theoretical foundation. The model describes the stochastic behavior of the system when the input signal is a stationary (stochastic) signal. In this paper the input is assumed to be white noise. Initial theoretical results are reported and validated with experimental data. 1