Online music libraries available on the Web contain a large amount of audio content that is usually the result of digitization of analogue recordings or the direct acquisition of digital sources. The acquisition process is carried out by several persons and may last a number of years, thus it is likely that the same or similar audio content is present in different versions. This paper describes a number of possible similarities, which are called affinities, and presents a methodology to detect the kind of affinity from the automatic analysis and matching of the audio content.
Searching and Classifying Affinities in a Web Music Collection
ORIO, NICOLA
2017
Abstract
Online music libraries available on the Web contain a large amount of audio content that is usually the result of digitization of analogue recordings or the direct acquisition of digital sources. The acquisition process is carried out by several persons and may last a number of years, thus it is likely that the same or similar audio content is present in different versions. This paper describes a number of possible similarities, which are called affinities, and presents a methodology to detect the kind of affinity from the automatic analysis and matching of the audio content.File in questo prodotto:
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