This paper addresses the problem of multi-pitch estimation, which consists in estimating the fundamental frequencies of multiple harmonic sources, with possibly overlapping partia...
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
In earlier work, Demaret and Iske proposed the scattered data coding (SDC) method for (single-rate) coding of arbitrarily-sampled image data. In this paper, several modifications...
For the first time, a proof of the sifting process (SP) and so the empirical mode decomposition (EMD), is given. For doing this, lower and upper envelopes are modeled in a more c...
El-Hadji Samba Diop, R. Alexandre, Abdel-Ouahab Bo...
We introduce a direct model for speech recognition that assumes an unstructured, i.e., flat text output. The flat model allows us to model arbitrary attributes and dependences o...
Georg Heigold, Geoffrey Zweig, Xiao Li, Patrick Ng...
In this paper we investigate the application of adaptive postfiltering for the enhancement of reverberant speech. The considered method is commonly used in Code Excited Linear Pr...
Automatic image tagging is important yet challenging due to the semantic gap and the lack of learning examples to model a tag’s visual diversity. Meanwhile, social user tagging ...
Abstract—Hyperspectral unmixing aims at identifying the hidden spectral signatures (or endmembers) and their corresponding proportions (or abundances) from an observed hyperspect...