Publications
Unsupervised Bayesian adaptation of PLDA for speaker verification
Summary
Summary
This paper presents a Bayesian framework for unsupervised domain adaptation of Probabilistic Linear Discriminant Analysis (PLDA). By interpreting class labels as latent random variables, Variational Bayes (VB) is used to derive a maximum a posterior (MAP) solution of the adapted PLDA model when labels are missing, referred to as VB-MAP...
PATHATTACK: attacking shortest paths in complex networks
Summary
Summary
Shortest paths in complex networks play key roles in many applications. Examples include routing packets in a computer network, routing traffic on a transportation network, and inferring semantic distances between concepts on the World Wide Web. An adversary with the capability to perturb the graph might make the shortest path...
Combating Misinformation: HLT Highlights from MIT Lincoln Laboratory
Summary
Summary
Dr. Joseph Campbell shares several human language technologies highlights from MIT Lincoln Laboratory. These include key enabling technologies in combating misinformation to link personas, analyze content, and understand human networks. Developing operationally relevant technologies requires access to corresponding data with meaningful evaluations, as Dr. Douglas Reynolds presented in his keynote...
Combating Misinformation: What HLT Can (and Can't) Do When Words Don't Say What They Mean
Summary
Summary
Misinformation, disinformation, and “fake news” have been used as a means of influence for millennia, but the proliferation of the internet and social media in the 21st century has enabled nefarious campaigns to achieve unprecedented scale, speed, precision, and effectiveness. In the past few years, there has been significant recognition...
Speaker separation in realistic noise environments with applications to a cognitively-controlled hearing aid
Summary
Summary
Future wearable technology may provide for enhanced communication in noisy environments and for the ability to pick out a single talker of interest in a crowded room simply by the listener shifting their attentional focus. Such a system relies on two components, speaker separation and decoding the listener's attention to...
Seasonal Inhomogeneous Nonconsecutive Arrival Process Search and Evaluation
Summary
Summary
Time series often exhibit seasonal patterns, and identification of these patterns is essential to understanding thedata and predicting future behavior. Most methods train onlarge datasets and can fail to predict far past the training data. This limitation becomes more pronounced when data is sparse. This paper presents a method to...
Automatic detection of influential actors in disinformation networks
Summary
Summary
The weaponization of digital communications and social media to conduct disinformation campaigns at immense scale, speed, and reach presents new challenges to identify and counter hostile influence operations (IO). This paper presents an end-to-end framework to automate detection of disinformation narratives, networks, and influential actors. The framework integrates natural language...
The Speech Enhancement via Attention Masking Network (SEAMNET): an end-to-end system for joint suppression of noise and reverberation [early access]
Summary
Summary
This paper proposes the Speech Enhancement via Attention Masking Network (SEAMNET), a neural network-based end-to-end single-channel speech enhancement system designed for joint suppression of noise and reverberation. It formalizes an end-to-end network architecture, referred to as b-Net, which accomplishes noise suppression through attention masking in a learned embedding space. A...
The 2019 NIST Speaker Recognition Evaluation CTS Challenge
Summary
Summary
In 2019, the U.S. National Institute of Standards and Technology (NIST) conducted a leaderboard style speaker recognition challenge using conversational telephone speech (CTS) data extracted from the unexposed portion of the Call My Net 2 (CMN2) corpus previously used in the 2018 Speaker Recognition Evaluation (SRE). The SRE19 CTS Challenge...
The 2019 NIST Audio-Visual Speaker Recognition Evaluation
Summary
Summary
In 2019, the U.S. National Institute of Standards and Technology (NIST) conducted the most recent in an ongoing series of speaker recognition evaluations (SRE). There were two components to SRE19: 1) a leaderboard style Challenge using unexposed conversational telephone speech (CTS) data from the Call My Net 2 (CMN2) corpus...