Being able to animate a speech production model with articulatory data would open applications in many domains. In this paper, we first consider the problem of acquiring articula...
M. Aron, Asterios Toutios, M.-O. Berger, E. Kerrie...
It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test da...
K-Means is a clustering algorithm that is widely applied in many elds, including pattern classi cation and multimedia analysis. Due to real-time requirements and computational-cos...
Training accurate acoustic models typically requires a large amount of transcribed data, which can be expensive to obtain. In this paper, we describe a novel semi-supervised learn...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
This paper proposes a method for adaptive speech dereverberation and speaker-position change detection, which have not previously been addressed. Signal transmission channels in r...
Sparse Decomposition (SD) of a signal on an overcomplete dictionary has recently attracted a lot of interest in signal processing and statistics, because of its potential applicat...
Massoud Babaie-Zadeh, Vincent Vigneron, Christian ...
CT The mobile internet has finally arrived with the sky-rocketing usage increase of HSPA. LTE, WiMAX and evolved WiFi are the upcoming wireless standards which are based on OFDM an...
This panel paper presents motivations for discussing mobile media search and contains statements from the panelists who are industry research leaders in this field.
Berna Erol, Jordan Cohen, Minoru Etoh, Hsiao-Wuen ...
We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift-invariant signal dictionari...