INTERSPEECH 2004 - ICSLP
In this paper we present a method of sound classification which exploits a parts-based representation of spectro-temporal sounds, employing the nonnegative matrix factorization (NMF). We illustrate a new way of learning nonnegative features using a variant of NMF and show its useful behavior in the task of general sound classification with comparison to independent component analysis (ICA) which produces holistic features.
Bibliographic reference. Cho, Yong-Choon / Choi, Seungjin (2004): "Learning nonnegative features of spectro-temporal sounds for classification", In INTERSPEECH-2004, 989-992.