activity
20192022
most citedA study of semi-supervised speaker diarization system using gan mixture model

3 citations · 6 across the 8 of their papers we have counts for

collaborators

12 papers

eess.AS20221 cited

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…

eess.AS2022

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…

eess.AS20212 cited

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…

eess.AS2021

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…

eess.IV2021

Disentanglement for audio-visual emotion recognition using multitask setup

Raghuveer Peri, Srinivas Parthasarathy, Charles Bradshaw +1

Deep learning models trained on audio-visual data have been successfully used to achieve state-of-the-art performance for emotion recognition. In particular, models trained with mu…

eess.AS2020

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…