3 citations · 6 across the 8 of their papers we have counts for
11 papers · 1 filter
Mel Frequency Spectral Domain Defenses against Adversarial Attacks on Speech Recognition Systems
Nicholas Mehlman, Anirudh Sreeram, Raghuveer Peri +1
A variety of recent works have looked into defenses for deep neural networks against adversarial attacks particularly within the image processing domain. Speech processing applicat…
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition
Raghuveer Peri, Krishna Somandepalli, Shrikanth Narayanan
Speaker recognition is increasingly used in several everyday applications including smart speakers, customer care centers and other speech-driven analytics. It is crucial to accura…
Perceptual-based deep-learning denoiser as a defense against adversarial attacks on ASR systems
Anirudh Sreeram, Nicholas Mehlman, Raghuveer Peri +2
In this paper we investigate speech denoising as a defense against adversarial attacks on automatic speech recognition (ASR) systems. Adversarial attacks attempt to force misclassi…
Automated Evaluation Of Psychotherapy Skills Using Speech And Language Technologies
Nikolaos Flemotomos, Victor R. Martinez, Zhuohao Chen +13
With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and…
Adversarial defense for deep speaker recognition using hybrid adversarial training
Monisankha Pal, Arindam Jati, Raghuveer Peri +3
Deep neural network based speaker recognition systems can easily be deceived by an adversary using minuscule imperceptible perturbations to the input speech samples. These adversar…
Adversarial Attack and Defense Strategies for Deep Speaker Recognition Systems
Arindam Jati, Chin-Cheng Hsu, Monisankha Pal +3
Robust speaker recognition, including in the presence of malicious attacks, is becoming increasingly important and essential, especially due to the proliferation of several smart s…