Publications
Advances in cross-lingual and cross-source audio-visual speaker recognition: The JHU-MIT system for NIST SRE21
Summary
Summary
We present a condensed description of the joint effort of JHUCLSP/HLTCOE, MIT-LL and AGH for NIST SRE21. NIST SRE21 consisted of speaker detection over multilingual conversational telephone speech (CTS) and audio from video (AfV). Besides the regular audio track, the evaluation also contains visual (face recognition) and multi-modal tracks. This...
Advances in speaker recognition for multilingual conversational telephone speech: the JHU-MIT system for NIST SRE20 CTS challenge
Summary
Summary
We present a condensed description of the joint effort of JHUCLSP/HLTCOE and MIT-LL for NIST SRE20. NIST SRE20 CTS consisted of multilingual conversational telephone speech. The set of languages included in the evaluation was not provided, encouraging the participants to develop systems robust to any language. We evaluated x-vector architectures...
Cross-language attacks
Summary
Summary
Memory corruption attacks against unsafe programming languages like C/C++ have been a major threat to computer systems for multiple decades. Various sanitizers and runtime exploit mitigation techniques have been shown to only provide partial protection at best. Recently developed ‘safe’ programming languages such as Rust and Go hold the promise...
Preventing Kernel Hacks with HAKCs
Summary
Summary
Commodity operating system kernels remain monolithic for practical and historical reasons. All kernel code shares a single address space, executes with elevated processor privileges, and has largely unhindered access to all data, including data irrelevant to the completion of a specific task. Applying the principle of least privilege, which limits...
Quantifying bias in face verification system
Summary
Summary
Machine learning models perform face verification (FV) for a variety of highly consequential applications, such as biometric authentication, face identification, and surveillance. Many state-of-the-art FV systems suffer from unequal performance across demographic groups, which is commonly overlooked by evaluation measures that do not assess population-specific performance. Deployed systems with bias...
Bayesian estimation of PLDA in the presence of noisy training labels, with applications to speaker verification
Summary
Summary
This paper presents a Bayesian framework for estimating a Probabilistic Linear Discriminant Analysis (PLDA) model in the presence of noisy labels. True class labels are interpreted as latent random variables, which are transmitted through a noisy channel, and received as observed speaker labels. The labeling process is modeled as a...
Tools and practices for responsible AI engineering
Summary
Summary
Responsible Artificial Intelligence (AI)—the practice of developing, evaluating, and maintaining accurate AI systems that also exhibit essential properties such as robustness and explainability—represents a multifaceted challenge that often stretches standard machine learning tooling, frameworks, and testing methods beyond their limits. In this paper, we present two new software libraries—hydra-zen and...
Adapting deep learning models to new meteorological contexts using transfer learning
Summary
Summary
Meteorological applications such as precipitation nowcasting, synthetic radar generation, statistical downscaling and others have benefited from deep learning (DL) approaches, however several challenges remain for widespread adaptation of these complex models in operational systems. One of these challenges is adequate generalizability; deep learning models trained from datasets collected in specific...
Keeping Safe Rust safe with Galeed
Summary
Summary
Rust is a programming language that simultaneously offers high performance and strong security guarantees. Safe Rust (i.e., Rust code that does not use the unsafe keyword) is memory and type safe. However, these guarantees are violated when safe Rust interacts with unsafe code, most notably code written in other programming...
Detecting pathogen exposure during the non-symptomatic incubation period using physiological data: proof of concept in non-human primates
Summary
Summary
Background and Objectives: Early warning of bacterial and viral infection, prior to the development of overt clinical symptoms, allows not only for improved patient care and outcomes but also enables faster implementation of public health measures (patient isolation and contact tracing). Our primary objectives in this effort are 3-fold. First...