Nonnegative Tensor Factorization for Directional Blind Audio Source Separation

Autor:	Stein, Noah D.
Rok vydání:	2014
Předmět:	Statistics - Machine Learning Computer Science - Learning
Druh dokumentu:	Working Paper
Popis:	We augment the nonnegative matrix factorization method for audio source separation with cues about directionality of sound propagation. This improves separation quality greatly and removes the need for training data, with only a twofold increase in run time. This is the first method which can exploit directional information from microphone arrays much smaller than the wavelength of sound, working both in simulation and in practice on millimeter-scale microphone arrays.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1411.5010 Zobrazit plný text záznamu View this record from Arxiv