This paper presents a novel method for solving the permutation problem inherent to frequency domain blind signal separation of multiple simultaneous speakers. As conventional meth...
Recent results seem to cast some doubt over the assumption that improvements in fused recognition accuracy for speaker recognition systems based on different acoustic features are...
Jia Min Karen Kua, Julien Epps, Mohaddeseh Nosrati...
This paper presents a novel method for audio event classi cation in overlapping conditions. The method is based on Jump Function Kolmogorov (JFK), a stochastic representation, whi...
In this paper, minimization of the statistical dependence is exploited for acoustic source localization purposes. Originally developed for the separation of signal mixtures, we sh...
Anthony Lombard, Yuanhang Zheng, Walter Kellermann
In semi-supervised classification boosting, a similarity measure is demanded in order to measure the distance between samples (both labeled and unlabeled). However, most of the e...