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Improving Instrumentality of Sound Collage Using CNMF Constraint Model

Authors: Miyaguchi, Sora; Osaka, Naotoshi; Ikeda, Yusuke;

Improving Instrumentality of Sound Collage Using CNMF Constraint Model

Abstract

In this study, the improvement in a new audio effect called sound collage, whereby one sound waveform (target sound) is synthesized using another sound waveform (elemental sound), is investigated. In this study, we propose a new model of convolutional NMF (CNMF) with constraints. And we compared the performance of three methods: the original CNMF, the new CNMF constraint model, and Driedger's NMF (non-negative matrix factorization method). Sound collage sounds are synthesized using a combination of animal calls as the target sound and several instrumental sounds as the elemental sounds. Psychological experiments are conducted to examine the degrees to which the target sound (reproducibility) and instrumental character (instrumentality) are represented. The results confirm that the instrumental nature of the synthesized sounds for both models improve compared with CNMF.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green