The paper presents a novel approach for voice activity detection. The main idea behind the presented approach is to use, next to the likelihood ratio of a statistical model-based voice activity detector, a set of informative distinct features in order to, via a supervised learning approach, enhance the detection performance. The statistical model-based voice activity detector, which is chosen b...

The problem of abrupt change detection has received much attention in the literature. The Neyman—Pearson detector can be derived and yields the well-known CUSUM algorithm, when the abrupt change is contaminated by an additive noise. However, a multiplicative noise has been observed in many signal processing applications. These applications include radar, sonar, communication and image processin...

Maximum and near-maximum likelihood sequence detectors in signal-dependent noise are discussed. It is shown that the linear prediction viewpoint allows a very simple derivation of the branch metric expression that has previously been shown as optimum for signal-dependent Markov noise. The resulting detector architecture is viewed as a noise predictive maximum likelihood detector that operates o...

This paper addresses the problem of detecting buried objects using a surface penetrating impulse radar. A big problem is that reeections from the ground surface will obscure the often much weaker target signal. The ground reeections and the target signal are mod-eled using a very simple model. This model is used to derive a detector based on a Likelihood Ratio Test, where unknown model paramete...

Instead of reduced-state decision-feedback sequence estimation (DFSE) equalization which is the state-of-the-art solution for the complexity reduction of the full-state Viterbi decoder over a fading multipath channel, we propose a new reducedcomplexity maximum likelihood sequence detector (MLSD) based on the particle filtering technique. The computational complexity of this new detector is adap...

It is well-known that the optimum multiuser detector achieves the global maximum likelihood (GML) detection in the entire set of hypotheses and several other iterative detectors such as the SAGE detector achieve the local maximum likelihood (LML) detection in the smallest neighborhood. In this paper, we generalize the local maximum likelihood detection into any size of neighborhood. The charact...

In this study, we investigate the problem of detecting time epochs when zero-velocity updates can be applied in a foot-mounted inertial navigation (motion tracking) system. We examine three commonly used detectors: the acceleration moving variance detector, the acceleration magnitude detector, and the angular rate energy detector. We demonstrate that all detectors can be derived within the same...

In This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture modeling, which is the speaker modeling tech...