DocumentCode :
23917
Title :
AutoMashUpper: Automatic Creation of Multi-Song Music Mashups
Author :
Davies, Matthew E. P. ; Hamel, Philippe ; Yoshii, Kazutomo ; Goto, Misako
Author_Institution :
Nat. Inst. of Adv. Ind. Sci. & Technol. (AIST), Tsukuba, Japan
Volume :
22
Issue :
12
fYear :
2014
fDate :
Dec. 2014
Firstpage :
1726
Lastpage :
1737
Abstract :
In this paper we present a system, AutoMashUpper, for making multi-song music mashups. Central to our system is a measure of “mashability” calculated between phrase sections of an input song and songs in a music collection. We define mashability in terms of harmonic and rhythmic similarity and a measure of spectral balance. The principal novelty in our approach centres on the determination of how elements of songs can be made fit together using key transposition and tempo modification, rather than based on their unaltered properties. In this way, the properties of two songs used to model their mashability can be altered with respect to transformations performed to maximize their perceptual compatibility. AutoMashUpper has a user interface to allow users to control the parameterization of the mashability estimation. It allows users to define ranges for key shifts and tempo as well as adding, changing or removing elements from the created mashups. We evaluate AutoMashUpper by its ability to reliably segment music signals into phrase sections, and also via a listening test to examine the relationship between estimated mashability and user enjoyment.
Keywords :
information retrieval; music; AutoMashUpper; automatic creation; harmonic similarity; key transposition; mashability estimation; mashability measurement; multisong music Mashups; music collection; perceptual compatibility; phrase sections; rhythmic similarity; tempo modification; Estimation; Feature extraction; Harmonic analysis; IEEE transactions; Mashups; Multiple signal classification; Spectrogram; Audio user interfaces; creative MIR; music remixing; music signal processing;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
2329-9290
Type :
jour
DOI :
10.1109/TASLP.2014.2347135
Filename :
6876193
Link To Document :
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