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Section: Events

Publication: IEEE Transactions on Multimedia

Manuscript Due: October 31, 2020 Publication Date: December 2021 CFP Document

Section: Our Story

McMaster University Ontario, Canada

Section: Our Story

University of Virginia Charlottesville, VA, USA

Section: Publications & Resources

In the past decade, deep learning methods have achieved unprecedented performance on a broad range of problems in various fields from computer vision to speech recognition. So far research has mainly focused on developing deep learning methods for Euclidean-structured data.

Section: Publications & Resources

The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Approximately one-fifth of the world's population suffer or have suffered from voice and speech production disorders due to diseases or some other dysfunction. Thus, there is a clear need for objective ways to evaluate the quality of voice and speech as well as its link to vocal fold activity, to evaluate the complex interaction between the larynx and voluntary movements of the articulators (i.e., lips, teeth, tongue, velum, jaw, etc), or to evaluate disfluencies at the language level.

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Obstructive Sleep Apnea (OSA) is a sleep breathing disorder affecting at least 3–7% of male adults and 2–5% of female adults between 30 and 70 years. It causes recurrent partial or total obstruction episodes at the level of the pharynx which causes cessation of breath during sleep. 

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Obstructive sleep apnea (OSA) is a sleep disorder in which pharyngeal collapse during sleep causes complete (apnea) or partial (hypopnea) airway obstruction. OSA is common and can have severe implications, but often remains undiagnosed. The most widely used objective measure of OSA severity is the number of obstructive events per hour of sleep, known as the apnea-hypopnea index (AHI).

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Clinical literature provides convincing evidence that language deficits in Alzheimer's disease (AD) allow for distinguishing patients with dementia from healthy subjects. Currently, computational approaches have widely investigated lexicosemantic aspects of discourse production, while pragmatic aspects like cohesion and coherence, are still mostly unexplored.

Section: Publications & Resources

Publication: IEEE Journal of Selected Topics in Signal Processing

Speech analysis could provide an indicator of Alzheimer's disease and help develop clinical tools for automatically detecting and monitoring disease progression. While previous studies have employed acoustic (speech) features for characterisation of Alzheimer's dementia, these studies focused on a few common prosodic features, often in combination with lexical and syntactic features which require transcription.