Acoustic-Labial Speaker Verification

This paper describes a multimodal approach for speaker verification. The system consists of two classifiers, one using visual features and the other using acoustic features. A lip tracker is used to extract visual information from the speaking face which provides shape and intensity features. We describe an approach for normalizing and mapping different modalities onto a common confidence interval. We also describe a novel method for integrating the scores of multiple classifiers. Verification experiments are reported for the individual modalities and for the combined classifier. The performance of the integrated system outperformed each sub-system and reduced the false acceptance rate of the acoustic sub-system from 2.3\% to 0.5\%

Fatigue in neuromuscular disorders: focus on Guillain–Barré syndrome and Pompe disease

Fatigue accounts for an important part of the burden experienced by patients with neuromuscular disorders. Substantial high prevalence rates of fatigue are reported in a wide range of neuromuscular disorders, such as Guillain–Barré syndrome and Pompe disease. Fatigue can be subdivided into experienced fatigue and physiological fatigue. Physiological fatigue in turn can be of central or peripheral origin. Peripheral fatigue is an important contributor to fatigue in neuromuscular disorders, but in reaction to neuromuscular disease fatigue of central origin can be an important protective mechanism to restrict further damage. In most cases, severity of fatigue seems to be related with disease severity, possibly with the exception of fatigue occurring in a monophasic disorder like Guillain–Barré syndrome. Treatment of fatigue in neuromuscular disease starts with symptomatic treatment of the underlying disease. When symptoms of fatigue persist, non-pharmacological interventions, such as exercise and cognitive behavioral therapy, can be initiated

Visual recognition of activities, gestures, facial expressions and speech: an introduction and a perspective

INTRODUCTION AND A PERSPECTIVE MUBARAK SHAH Computer Vision Lab Computer ScienceDepartment University of Central Florida Orlando, FL 32816 AND RAMESH JAIN Electrical and Computer Engineering University of California, San Diego La Jolla, CA 92093-0407 1. Introduction Computer vision has started migrating from the peripheral area to the core of computer science and engineering. Multimedia computing and natural human-machine interfaces are providing adequate challenges and motivation to develop techniques that will playkey role in the next generation of computing systems. Recognition of objects and events is very importantin multimedia systems as well as interfaces. We consider an object a spatial entity and an eventatemporal entity. Visual recognition of objects and activities is one of the fastest developing area of computer vision. Objects and events must be recognized by analyzing images. A