Monophonic sound source separation by non-negative sparse autoencoders

Monophonic sound source separation is an essential subject on the fields where sound, such as voice, music and noise, is dealt with. In particular, unsupervised approaches to this problem have high versatility in comparison with supervised approaches. Non-negative matrix factorization is the most fr...

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Veröffentlicht in:	Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics S. 3623 - 3626
Hauptverfasser:	Zen, Keiki, Suzuki, Masahiro, Sato, Haruhiko, Oyama, Satoshi, Kurihara, Masahito
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.01.2014
Schlagworte:	Artificial neural networks Image reconstruction IP networks monophonic sound source separation Neurons NMF non-negative sparse autoencoder online learning Source separation Sparse matrices unsupervised learning Vectors
ISSN:	1062-922X
Online-Zugang:	Volltext
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