Adversarial Black-Box Attacks on Automatic Speech Recognition Systems using Multi-Objective Evolutionary Optimization

Fooling deep neural networks with adversarial input have exposed a significant vulnerability in the current state-of-the-art systems in multiple domains. Both black-box and white-box approaches have been used to either replicate the model itself or to craft examples which cause the model to fail. In this work, we propose a framework which uses multi-objective evolutionary optimization to perform both targeted and un-targeted black-box attacks on Automatic Speech Recognition (ASR) systems. We apply this framework on two ASR systems: Deepspeech and Kaldi-ASR, which increases the Word Error Rates (WER) of these systems by upto 980%, indicating the potency of our approach. During both un-targeted and targeted attacks, the adversarial samples maintain a high acoustic similarity of 0.98 and 0.97 with the original audio.Comment: Published in Interspeech 201

Should We Screen for Depression in the Emergency Department?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73525/1/j.1553-2712.2004.tb01430.x.pd

A Visual Programming Paradigm for Abstract Deep Learning Model Development

Deep learning is one of the fastest growing technologies in computer science with a plethora of applications. But this unprecedented growth has so far been limited to the consumption of deep learning experts. The primary challenge being a steep learning curve for learning the programming libraries and the lack of intuitive systems enabling non-experts to consume deep learning. Towards this goal, we study the effectiveness of a no-code paradigm for designing deep learning models. Particularly, a visual drag-and-drop interface is found more efficient when compared with the traditional programming and alternative visual programming paradigms. We conduct user studies of different expertise levels to measure the entry level barrier and the developer load across different programming paradigms. We obtain a System Usability Scale (SUS) of 90 and a NASA Task Load index (TLX) score of 21 for the proposed visual programming compared to 68 and 52, respectively, for the traditional programming methods

Hi, how can I help you?: Automating enterprise IT support help desks

Question answering is one of the primary challenges of natural language understanding. In realizing such a system, providing complex long answers to questions is a challenging task as opposed to factoid answering as the former needs context disambiguation. The different methods explored in the literature can be broadly classified into three categories namely: 1) classification based, 2) knowledge graph based and 3) retrieval based. Individually, none of them address the need of an enterprise wide assistance system for an IT support and maintenance domain. In this domain the variance of answers is large ranging from factoid to structured operating procedures; the knowledge is present across heterogeneous data sources like application specific documentation, ticket management systems and any single technique for a general purpose assistance is unable to scale for such a landscape. To address this, we have built a cognitive platform with capabilities adopted for this domain. Further, we have built a general purpose question answering system leveraging the platform that can be instantiated for multiple products, technologies in the support domain. The system uses a novel hybrid answering model that orchestrates across a deep learning classifier, a knowledge graph based context disambiguation module and a sophisticated bag-of-words search system. This orchestration performs context switching for a provided question and also does a smooth hand-off of the question to a human expert if none of the automated techniques can provide a confident answer. This system has been deployed across 675 internal enterprise IT support and maintenance projects.Comment: To appear in IAAI 201

Actionable Insights on Philadelphia Crime Hot-Spots: Clustering and Statistical Analysis to Inform Future Crime Legislation

Philadelphia's problem with high crime rates continues to be exacerbated as Philadelphia's residents, community leaders, and law enforcement officials struggle to address the root causes of the problem and make the city safer for all. In this work, we deeply understand crime in Philadelphia and offer novel insights for crime mitigation within the city. Open source crime data from 2012-2022 was obtained from OpenDataPhilly. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) was used to cluster geographic locations of crimes. Clustering of crimes within each of 21 police districts was performed, and temporal changes in cluster distributions were analyzed to develop a Non-Systemic Index (NSI). Home Owners' Loan Corporation (HOLC) grades were tested for associations with clusters in police districts labeled `systemic.' Crimes within each district were highly clusterable, according to Hopkins' Mean Statistics. NSI proved to be a good measure of differentiating systemic ($<$ 0.06) and non-systemic ($\geq$ 0.06) districts. Two systemic districts, 19 and 25, were found to be significantly correlated with HOLC grade (p $=2.02 \times 10^{-19}$, p $=1.52 \times 10^{-13}$). Philadelphia crime data shows a high level of heterogeneity between districts. Classification of districts with NSI allows for targeted crime mitigation strategies. Policymakers can interpret this work as a guide to interventions

Resident Perceptions of Medical Errors in the Emergency Department

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73541/1/S1069-6563_03_00559-1.pd

Conjoint bicondylar Hoffa fracture in a child: a rare variant treated by minimally invasive approach

A case of conjoint Hoffa-type fracture in a child is presented. Hoffa fracture, i.e., coronal slice fracture of the condyles of the femur, is rare in adults and even rarer in the pediatric population. To date, no case of conjoint bicondylar Hoffa fracture has been reported in the literature. The presented case was successfully treated by arthroscopically assisted internal fixation

Knowledge Translation Consensus Conference: Research Methods

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72708/1/j.1553-2712.2007.tb02378.x.pd

Tuberculous extensor tenosynovitis of the wrist with extensor pollicis longus rupture: a case report

<p>Abstract</p> <p>Introduction</p> <p>The tendon sheaths constitute an uncommon target of extra-articular tuberculosis.</p> <p>Case presentation</p> <p>We present a rare case of tuberculous tenosynovitis of the wrist involving the extensor tendon with rupture of the extensor pollicis longus tendon in a 55-year-old Indian man.</p> <p>Conclusion</p> <p>Prompt surgical debridement and tissue diagnosis are essential for the diagnosis and treatment of this type of infection. With an accurate and timely diagnosis, appropriate surgery and antituberculous treatment may eradicate these infections and prevent complications.</p