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IEEE Symposium on 3D User Interfaces (3DUI)

作者： Wallace Lages Mahdi Nabiyouni Javier Tibau Doug A. Bowman Department of Computer Science Center for Human Computer Interaction

We present a novel virtual musical instrument interface based on in-air 3D gestures called the Interval Player. Instead of specifying absolute notes, the user specifies the melodic interval between the most recent note and the next one. The non-dominant hand is used to specify chords for harmony. We discuss the principles and rationale used in the design.

关键词： Thumb Music Instruments Training Lead

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DISCRIMINATIVELY TRAINED JOINT SPEAKER AND ENVIRONMENT REPRESENTATIONS FOR ADAPTATION OF DEEP NEURAL NETWORK ACOUSTIC MODELS

DISCRIMINATIVELY TRAINED JOINT SPEAKER AND ENVIRONMENT REPRE...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Maofan Yin Sunil Sivadas Kai Yu Bin Ma Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering SpeechLab. Department of Computer Science and Engineering Shanghai Jiao Tong University China Human Language Technology Lab. Institute for Infocomm Research Singapore

ISBN: (纸本)9781479999897

A recent trend in normalization of factors extraneous to a speech recognition task has been to explicitly introduce features related to the unwanted variability in the training of Deep Neural Networks (DNN). Typically, this is done by either perturbing the training set with models of these extraneous factors such as vocal tract length and environmental noise or augmenting the conventional spectral features with auxiliary information such as i-vector, noise spectrum, etc. Another emerging approach is to derive low dimensional representations of the factors from the hidden layers of DNN and use it for normalization of the acoustic model. Almost all of these approaches focus on either speaker or environment normalization. In this paper we propose a novel approach for estimating a compact joint representation of speakers and environment by training a DNN, with a bottleneck layer, to classify the i-vector features into speaker and environment labels by Multi-Task Learning (MTL). Another novelty is to learn this compact representation while learning to map the i-vector of a noisy utterance into its corresponding clean speaker ivector and noise-only i-vector. Experiments were conducted on an artificially noise-corrupted version of the WSJ corpus. The proposed compact joint speaker-environment representations show promising gains.

关键词： i-vector deep neural network speaker adaptation multi-task learning noise robustness Loudspeakers speaker adaptation Noise robustness Environments normalization Joints Neural network representations Speech recognition PARALLEL PROCESSING (computerS) Acoustic models Ambient Noise Vocal tract

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Global brain dynamics during social exclusion predict subsequent behavioral conformity

arXiv

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arXiv 2017年

作者： Wasylyshyn, Nick Hemenway, Brett Garcia, Javier O. Cascio, Christopher N. O'Donnell, Matthew Brook Raymond Bingham, C. Simons-Morton, Bruce Vettel, Jean M. Falk, Emily B. Human Research and Engineering Directorate U.S. Army Research Laboratory Aberdeen Proving GroundMD21005 Annenberg School for Communication University of Pennsylvania PhiladelphiaPA19104 Department of Computer and Information Science University of Pennsylvania PhiladelphiaPA19104 Department of Bioengineering University of Pennsylvania PhiladelphiaPA19104 University of Michigan Transportation Research Institute Ann ArborMI48109 Eunice Kennedy Shriver National Institute on Child Health and Human Development BethesdaMD20892 Department of Psychological and Brain Sciences University of California Santa Barbara Santa BarbaraCA93106 Marketing Department Wharton School University of Pennsylvania University of Pennsylvania PhiladelphiaPA19104 Department of Psychology University of Pennsylvania PhiladelphiaPA19104

Individuals react differently to social experiences;for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt their behavior to fit in with others. We examined whether functional brain connectivity during social exclusion in the fMRI scanner can be used to predict subsequent conformity to peer norms. Adolescent males (N = 57) completed a two-part study on teen driving risk: a social exclusion task (Cyberball) during an fMRI session and a subsequent driving simulator session in which they drove alone and in the presence of a peer who expressed risk-averse or risk-accepting driving norms. We computed the difference in functional connectivity between social exclusion and social inclusion from each node in the brain to nodes in two brain networks, one previously associated with mentalizing (medial prefrontal cortex, temporoparietal junction, precuneus, temporal poles) and another with social pain (anterior cingulate cortex, anterior insula). Using cross-validated machine learning, this measure of global network connectivity during exclusion predicts the extent of conformity to peer pressure during driving in the subsequent experimental session. These findings extend our understanding of how global neural dynamics guide social behavior, revealing functional network activity that captures individual differences. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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Malware in the future? forecasting of analyst detection of cyber events

arXiv

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arXiv 2017年

作者： Bakdash, Jonathan Z. Hutchinson, Steve Zaroukian, Erin G. Marusich, Laura R. Thirumuruganathan, Saravanan Sample, Charmaine Hoffman, Blaine Das, Gautam U.S. Army Research Laboratory South The University of Texas Dallas RichardsonTX United States Department of Psychology Counseling and Special Education Texas A&M Commerce Commerce TX United States Computational and Information Sciences Directorate ICF for the U.S. Army Research Laboratory AdelphiMD United States Human Research and Engineering Directorate U.S. Army Research Laboratory Aberdeen Proving Ground MD United States U.S. Army Research Laboratory South The University of Texas Arlington ArlingtonTX United States Qatar Computing and Research Institute Qatar Foundation Doha Qatar Computer Science and Engineering Department University of Texas Arlington ArlingtonTX United States

Cyber attacks endanger physical, economic, social, and political security. There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate such cyber attacks. A common approach is time-series forecasting of cyber attacks based on data from network telescopes, honeypots, and automated intrusion detection/prevention systems. This research has uncovered key insights such as systematicity in cyber attacks. Here, we propose an alternate perspective of this problem by performing forecasting of attacks that are analyst-detected and -verified occurrences of malware. We call these instances of malware cyber event data. Specifically, our dataset was analyst-detected incidents from a large operational computer Security Service Provider (CSSP) for the U.S. department of Defense, which rarely relies only on automated systems. Our data set consists of weekly counts of cyber events over approximately seven years. This curated dataset has characteristics that distinguish it from most datasets used in prior research on cyber attacks. Since all cyber events were validated by analysts, our dataset is unlikely to have false positives which are often endemic in other sources of data. Further, the higher-quality data could be used for a number of important tasks for CSSPs such as resource allocation, estimation of security resources, and the development of effective risk-management strategies. To quantify bursts, we used a Markov model of state transitions. For forecasting, we used a Bayesian State Space Model and found that events one week ahead could be predicted with reasonable accuracy, with the exception of bursts. Our findings of systematicity in analyst-detected cyber attacks are consistent with previous work using cyber attack data from other sources. The advanced information provided by a forecast may help with threat awareness by providing a probable value and range for future cyber events one week ahead, similar to a weather foreca

关键词： Network security

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Towards a unified definition of web accessibility 12

Towards a unified definition of web accessibility

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12th International Web for All Conference, W4A 2015

作者： Petrie, Helen Savva, Andreas Power, Christopher Human Computer Interaction Research Group University of York Department of Computer Science Deramore Lane Heslington-East-YorkYO10 5GH United Kingdom

ISBN: (纸本)9781450333429

To better understand what researchers and practitioners consider to be the key components of the definition of web accessibility and to propose a unified definition of web accessibility, we conducted an analysis of 50 definitions of web accessibility. The definitions were drawn from a range of books, papers, standards, guidelines and online sources, aimed at both practitioners and researchers, from the across the time period of web accessibility work, from 1996 to 2014 and from authors in 21 different countries. The analysis extracted six core concepts that are used in many definitions, which are incorporated into a unified definition of web accessibility as "all people, particularly disabled and older people, can use websites in a range of contexts of use, including mainstream and assistive technologies;to achieve this, websites need to be designed and developed to support usability across these contexts". Copyright 2015 ACM.

关键词： Websites

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Comparing the performance of natural, semi-natural, and non-natural locomotion techniques in virtual reality

Comparing the performance of natural, semi-natural, and non-...

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IEEE Annual International Symposium Virtual Reality

作者： Mahdi Nabiyouni Ayshwarya Saktheeswaran Doug A. Bowman Ambika Karanth Center for Human-Computer Interaction and Department of Computer Science Virginia Tech

One of the goals of much virtual reality (VR) research is to increase realism. In particular, many techniques for locomotion in VR attempt to approximate real-world walking. However, it is not yet fully understood how the design of more realistic locomotion techniques affects user task performance. We performed an experiment to compare a semi-natural locomotion technique (based on the Virtusphere device) with a traditional, non-natural technique (based on a game controller) and a fully natural technique (real walking). We found that the Virtusphere technique was significantly slower and less accurate than both of the other techniques. Based on this result and others in the literature, we speculate that locomotion techniques with moderate interaction fidelity will often have performance inferior to both high-fidelity techniques and well-designed low-fidelity techniques. We argue that our experimental results are an effect of interaction fidelity, and perform an analysis of the fidelity of the three locomotion techniques to support this argument.

关键词： Legged locomotion Virtual reality Games Performance evaluation human computer interaction Standards

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Design and evaluation of a visual acclimation aid for a semi-natural locomotion device

Design and evaluation of a visual acclimation aid for a semi...

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IEEE Symposium on 3D User Interfaces (3DUI)

作者： Mahdi Nabiyouni Siroberto Scerbo Vincent DeVito Stefan Smolen Patrick Starrin Doug A. Bowman Center for Human-Computer Interaction and Department of Computer Science Virginia Tech

ISBN: (纸本)9781467368872

One of the limitations of most virtual reality (VR) systems is that users cannot physically walk through large virtual environments. Many solutions have been proposed to this problem, including locomotion devices such as the Virtusphere. Such devices allow the user to employ moderately natural walking motions without physically moving through space, but may actually be difficult to use at first due to a lack of interaction fidelity. We designed and evaluated a visual aid that shows a virtual representation of the sphere to the user during an acclimation phase, reasoning that this would help users understand the forces they were feeling, plan their movements, and better control their movements. In a user study, we evaluated participants' walking performance both during and after an acclimation phase. Half of the participants used the visual aid during acclimation, while the other half had no visual aid. After acclimation, all participants performed more complex walking assessment tasks without any visual aid. The results demonstrate that use of the visual aid during acclimation was effective for improving task performance and decreasing perceived difficulty in the assessment tasks.

关键词： Visualization Legged locomotion Training Virtual reality User interfaces Games Performance evaluation

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Binary hologram generation of real objects by combination of color and depth map

Binary hologram generation of real objects by combination of...

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Euro-American Workshop on Information Optics (WIO)

作者： Thibault Leportier Min-Chul Park Kwang-hoon Lee Department of Human Computer Interaction and Robotics Korea University of Science and Technology Seoul South Korea Center of Opto- Electronic Materials and Devices Korea Institute of Science and Technology Seoul South Korea 3D convergence research center Korea Photonics Technology Institute Gwangju South Korea

ISBN: (纸本)9781509021642

Holograms can be captured optically or computed numerically. Optical methods enable to record information of real objects as they are, but high stability and dark room conditions for experimental set-up is required. It often restricts the capture to only small shape objects. On the other hand, computer Generated Hologram (CGH) approach enables to calculate complex hologram in a flexible way. The scale of the scene can be set as well as the viewing distance or the resolution. The main challenges are to overcome the heavy computational burden and to provide a good sense of reality. CGHs can be calculated from point clouds or polygon models. With this approach, the contributions of every element should be computed for every pixels of the hologram. Holographic data can also be computed by applying propagation formula on 2D images, but the phase should be determined and as well as the depth position at every pixel. We exploited a Kinect camera that has raised a lot of interest recently since it enables to scan a scene for 3D modeling, or to capture both depth map and RGB frame of a scene. Depth map can be used to extract phase information. Combined with the amplitude image, complex field can be determined in a given plane. Then, CGH can be computed in a fast way. For the display part, Direct Binary Search (DBS) algorithm was applied to convert CGH of real scene into binary format so that bandwidth of the SLM can be fully exploited.

关键词： Image reconstruction Optical imaging Satellite broadcasting Optical reflection Three-dimensional displays Holography Optical sensors

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EEG-based user reaction time estimation using riemannian geometry features

arXiv

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arXiv 2017年

作者： Wu, Dongrui Lance, Brent J. Lawhern, Vernon J. Gordon, Stephen Jung, Tzyy-Ping Link, Chin-Teng DataNova NY United States Human Research and Engineering Directorate U.S. Army Research Laboratory Aberdeen Proving GroundMD United States Department of Computer Science University of Texas at San Antonio San AntonioTX United States Dcs Corp AlexandriaVA United States Swartz Center for Computational Neuroscience Center for Advanced Neurological Engineering University of California San Diego La JollaCA United States Centre for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Australia

Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for Electroencephalogram (EEG) based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30-8.30%, and increase the estimation correlation coefficient by 6.59-11.13%. Copyright © 2017, The Authors. All rights reserved.

关键词： Brain computer interface

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Exploring the neurocircuitry underpinning predictability of threat in soldiers with PTSD compared to deployment exposed controls

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Open Neuroimaging Journal 2016年 10卷 111-124页

作者： Dretsch, Michael N. Wood, Kimberly H. Daniel, Thomas A. Katz, Jeffrey S. Deshpande, Gopikrishna Goodman, Adam M. Wheelock, Muriah D. Wood, Kayli B. Denney, Thomas S. Traynham, Stephanie Knight, David C. U.S. Army Aeromedical Research Laboratory Fort Rucker AL United States Human Dimension Division HQ TRADOC 950 Jefferson Ave Fort Eustis 23604 VA United States Department of Psychology University of Alabama Birmingham AL United States Department of Psychology Auburn University Auburn AL United States Oak Ridge Institute for Science and Education Oak Ridge TN United States AU MRI Research Center Department of Electrical and Computer Engineering Auburn University Auburn AL United States

Background: Prior work examining emotional dysregulation observed in posttraumatic stress disorder (PTSD) has primarily been limited to fearlearning processes specific to anticipation, habituation, and extinction of threat. In contrast, the response to threat itself has not been systematically evaluated. Objective: To explore potential disruption in fear conditioning neurocircuitry in service members with PTSD, specifically in response to predictable versus unpredictable threats. Method: In the current study, active-duty U.S. Army soldiers with (PTSD group;n = 38) and without PTSD (deployment-exposed controls;DEC;n = 40), participated in a fear-conditioning study in which threat predictability was manipulated by presenting an aversive unconditioned stimulus (UCS) that was either preceded by a conditioned stimulus (i.e., predictable) or UCS alone (i.e., unpredictable). Threat expectation, skin conductance response (SCR), and functional magnetic resonance imaging (fMRI) signal to predictable and unpredictable threats (i.e., UCS) were assessed. Results: Both groups showed greater threat expectancy and diminished threat-elicited SCRs to predictable compared to unpredictable threat. Significant group differences were observed within the amygdala, hippocampus, insula, and superior and middle temporal gyri. Contrary to our predictions, the PTSD group showed a diminished threat-related response within each of these brain regions during predictable compared to unpredictable threat, whereas the DEC group showed increased activation. Conclusion: Although, the PTSD group showed greater threat-related diminution, hypersensitivity to unpredictable threat cannot be ruled out. Furthermore, pre-trauma, trait-like factors may have contributed to group differences in activation of the neurocircuitry underpinning fear conditioning. © Dretsch et al.

关键词： Amygdala Fear-conditioning Hippocampus Insula Military Neuroimaging PTSD

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