Sound field reproduction methods like higher order Ambisonics which are based on orthogonal expansions always introduce a limitation of the spatial bandwidth of the secondary sou...
Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse respo...
An important parameter in analysis of physiological tremor is the diagnosis and study of neurological disorders. The instantaneous tremor frequency (ITF) is an important parameter...
Alp Kucukelbir, Azadeh Kushki, Konstantinos N. Pla...
We investigate genre effects on the task of automatic sentence segmentation, focusing on two important domains – broadcast news (BN) and broadcast conversation (BC). We employ a...
Quickest detection of an abrupt distribution change with an unknown time varying parameter is considered. A novel adaptive approach is proposed to tackle this problem, which is sh...
In this paper, we re-examine the recently proposed distributed state estimators based on quantized innovations. It is widely believed that the error covariance of the Quantized In...
In this paper we propose discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition tasks. After presenting our hierarchical modeli...
This paper proposes a distributed representation algorithm for multi-view images that are jointly reconstructed at the decoder. Compressed versions of each image are first obtain...
In this paper, we consider the extraction of speaker identity from audio records of broadcast news without a priori acoustic information about speakers. Using an automatic speech ...
Vincent Jousse, Simon Petit-Renaud, Sylvain Meigni...
We present an algorithm for active learning (adaptive selection of training data) within the context of semi-supervised multi-task classifier design. The semi-supervised multi-ta...