Publications

The decreasing costs and increasing speed and accuracy of DNA sample collection, preparation, and sequencing has rapidly produced an enormous volume of genetic data. However, fast and accurate analysis of the samples remains a bottleneck. Here we present D4RAGenS, a genetic sequence identification algorithm that exhibits the Big Data handling...

Current metagenomic analysis algorithms require significant computing resources, can report excessive false positives (type I errors), may miss organisms (type II errors/false negatives), or scale poorly on large datasets. This paper explores using big data database technologies to characterize very large metagenomic DNA sequences in protein space, with the ultimate...

Recent technological advances in Next Generation Sequencing tools have led to increasing speeds of DNA sample collection, preparation, and sequencing. One instrument can produce over 600 Gb of genetic sequence data in a single run. This creates new opportunities to efficiently handle the increasing workload. We propose a new method...

We introduce a framework for speech enhancement based on convolutive non-negative matrix factorization that leverages available speech data to enhance arbitrary noisy utterances with no a priori knowledge of the speakers or noise types present. Previous approaches have shown the utility of a sparse reconstruction of the speech-only components of...

A hypothesis in characterizing human depression is that change in the brain's basal ganglia results in a decline of motor coordination. Such a neuro-physiological change may therefore affect laryngeal control and dynamics. Under this hypothesis, toward the goal of objective monitoring of depression severity, we investigate vocal-source biomarkers for depression...

The NIST speaker recognition evaluation (SRE) featured microphone data in the 2005-2010 evaluations. The preprocessing and use of this data has typically been performed with telephone bandwidth and quantization. Although this approach is viable, it ignores the richer properties of the microphone data-multiple channels, high-rate sampling, linear encoding, ambient noise...

Of increasing importance in the civilian and military population is the recognition of Major Depressive Disorder at its earliest stages and intervention before the onset of severe symptoms. Toward the goal of more effective monitoring of depression severity, we investigate automatic classifiers of depression state, that have the important property...

Regions of nonmodal phonation, exhibiting deviations from uniform glottal-pulse periods and amplitudes, occur often and convey information about speaker- and linguistic-dependent factors. Such waveforms pose challenges for speech modeling, analysis/synthesis, and processing. In this paper, we investigate the representation of nonmodal pulse trains as a sum of harmonically-related sinewaves with...

Of increasing importance in the civilian and military population is the recognition of major depressive disorder at its earliest stages and intervention before the onset of severe symptoms. Toward the goal of more effective monitoring of depression severity, we introduce vocal biomarkers that are derived automatically from phonologically-based measures of...

One of the most significant air traffic challenges is managing the National Airspace System (NAS) in a manner that optimizes efficiency and mitigates avoidable delay, while maintaining safety, when convective weather is present. To do this, aviation planners seek to develop strategic air traffic management (ATM) plans and initiatives that...