A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness

no code implementations • 18 Dec 2022 • Tiantian Feng, Rajat Hebbar, Nicholas Mehlman, Xuan Shi, Aditya Kommineni, and Shrikanth Narayanan

Speech-centric machine learning systems have revolutionized many leading domains ranging from transportation and healthcare to education and defense, profoundly changing how people live, work, and interact with each other.

Fairness

Mel Frequency Spectral Domain Defenses against Adversarial Attacks on Speech Recognition Systems

no code implementations • 29 Mar 2022 • Nicholas Mehlman, Anirudh Sreeram, Raghuveer Peri, Shrikanth Narayanan

A variety of recent works have looked into defenses for deep neural networks against adversarial attacks particularly within the image processing domain.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Perceptual-based deep-learning denoiser as a defense against adversarial attacks on ASR systems

no code implementations • 12 Jul 2021 • Anirudh Sreeram, Nicholas Mehlman, Raghuveer Peri, Dillon Knox, Shrikanth Narayanan

In this paper we investigate speech denoising as a defense against adversarial attacks on automatic speech recognition (ASR) systems.

Adversarial Robustness Automatic Speech Recognition +4