We applied a multiple kernel learning (MKL) method based on information-theoretic optimization to speaker recognition. Most of the kernel methods applied to speaker recognition sy...
Tetsuji Ogawa, Hideitsu Hino, Nima Reyhani, Noboru...
Spectral factorization is a classical tool in signal processing and communications. It also plays a critical role in X-ray crystallography, in the context of phase retrieval. In t...
We present fundamental concepts of risk and propose two methods for risk management of a portfolio in this paper. Moreover, we introduce their novel extensions to trading in multi...
We address the problem of pronunciation variation in conversational speech with a context-dependent articulatory featurebased model. The model is an extension of previous work usi...
Preethi Jyothi, Karen Livescu, Eric Fosler-Lussier
We consider the problem of channel estimation for amplify-andforward (AF) two-way relay networks (TWRNs). The majority of works on this problem develop pilot-based algorithms that...
Traditional channel quantization based methods for encryption key generation usually suffer from the quantization error which may decrease the key agreement ratio between authoriz...
In this paper, we revisit the noise-reduction problem in the time domain and present a way to decompose the ltered speech into two uncorrelated (orthogonal) components: the desire...
Jingdong Chen, Jacob Benesty, Yiteng Huang, Tomas ...
In this paper, we present the Gauss-Newton method as a unified approach to optimizing non-linear noise compensation models, such as vector Taylor series (VTS), data-driven parall...
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...
We consider spatio-temporal Tomlinson Harashima Precoding where the feedforward filter is located at the transmitter and an additional scalar gain is employed as receive filter....