Publications
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Unsupervised Learning of Acoustic Units Using Autoencoders and Kohonen Nets
This work investigates learning acoustic units in an unsupervised manner from real-world speech data by using a cascade of an autoencoder and a Kohonen net.
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On the Issue of Calibration in DNN-Based Speaker Recognition Systems
This article is concerned with the issue of calibration in the context of Deep Neural Network (DNN) based approaches to speaker recognition. We propose a hybrid alignment framework, which stems…
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Fusion Strategies for Robust Speech Recognition and Keyword Spotting for Channel- and Noise-Degraded Speech
Current state-of-the-art automatic speech recognition systems are sensitive to changing acoustic conditions, which can cause significant performance degradation.
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Intelligent Coaching Systems in Higher-Order Applications: Lessons from Automated Content Creation Bottlenecks
This presentation describes two projects for interactive training that developed prototypes for automated content creation plus a third project that illustrates a suite of learning object libraries to support engineering…
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Course-Taking Effect on Postsecondary Enrollment of Deaf and Hard of Hearing Students
Data from the National Longitudinal Transition Study-2 were used to examine the effect of academic and career or technical education course-taking in high school on deaf or hard of hearing…
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Integrated Digital Printing of Flexible Circuits for Wireless Sensing
At PARC, we combine high functionality c-Si CMOS and digitally printed components and interconnects to create an integrated platform that can read and process multiple discrete sensors.
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Additive Manufacturing of Functionally Graded Objects: A Review
In this paper, we focus on providing an overview of research at the intersection of AM techniques and FGM objects.
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Relational Similarity Machines
In this work, we propose Relational Similarity Machines (RSM) a fast, accurate, and flexible relational learning framework for supervised and semi-supervised classification problems.
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Can low-Cost online summer math programs improve student preparation for college-level math? Evidence from randomized experiments at three universities
We conducted randomized experiments of low-cost online summer math programs to test whether this type of intervention can increase access to math preparation, improve placement and enrollment in fall math…
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Analyzing hyperspectral images into multiple subspaces using Guassian mixture models
I argue that the spectra in a hyperspectral datacube will usually lie in several low dimensional subspaces, and that these subspaces are more easily estimated from the data than the…
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Trust in Content-Centric Networking: From Theory to Practice
We present the logical design of a trust engine for Information-Centric Networking (ICN) that is capable of efficiently and correctly verifying content integrity and authenticity.
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Improving early literacy in PreK–3: Lessons learned (August 2016)
The Pathway Schools Initiative aims to dramatically increase the number of students who reach the critical milestone of grade 3 reading proficiency, an indicator predictive of later academic outcomes and…