Many sensor network related applications require precise knowledge of the location of constituent nodes. In these applications, it is desirable for the wireless nodes to be able t...
This paper proposes a noise robust exemplar-based speech recognition system where noisy speech is modeled as a linear combination of a set of speech and noise exemplars. The metho...
Class posterior distributions have recently been used quite successfully in Automatic Speech Recognition (ASR), either for frame or phone level classification or as acoustic featu...
Data sparseness is an ever dominating problem in automatic emotion recognition. Using artificially generated speech for training or adapting models could potentially ease this: t...
A new dictionary selection approach for sparse coding, called parametric dictionary design, has recently been introduced. The aim is to choose a dictionary from a class of admissi...
Mehrdad Yaghoobi, Laurent Daudet, Michael E. Davie...
In this paper we propose two fast Total Variation (TV) based algorithms for image restoration by utilizing variational posterior distribution approximation. The unknown image and ...
Bruno Amizic, S. Derin Babacan, K. Michael Ng, Raf...
Applications to evaluate Internet quality-of-service and increase network security are essential to maintaining reliability and high performance in computer networks. These applic...
—This paper provides a framework for designing space-time codes to take advantage of a small number of feedback bits from the receiver. The new codes are based on circulant matri...
Compressive-sensing cameras are an important new class of sensors that have different design constraints than standard cameras. Surprisingly, little work has explored the relation...
This paper presents the results of formant analysis using a newly developed formant contour model. We model formant contours with a linear combination of formant target values and...