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20172022
most citedSpeaker Diarization with Lexical Information

28 citations · 97 across the 30 of their papers we have counts for

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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.AS2021

Front-end Diarization for Percussion Separation in Taniavartanam of Carnatic Music Concerts

Nauman Dawalatabad, Jilt Sebastian, Jom Kuriakose +3

Instrument separation in an ensemble is a challenging task. In this work, we address the problem of separating the percussive voices in the taniavartanam segments of Carnatic music…

eess.AS2021

End-to-End Neural Systems for Automatic Children Speech Recognition: An Empirical Study

Prashanth Gurunath Shivakumar, Shrikanth Narayanan

A key desiderata for inclusive and accessible speech recognition technology is ensuring its robust performance to children's speech. Notably, this includes the rapidly advancing ne…

eess.AS2020

Multi-Scale Speaker Diarization With Neural Affinity Score Fusion

Tae Jin Park, Manoj Kumar, Shrikanth Narayanan

Identifying the identity of the speaker of short segments in human dialogue has been considered one of the most challenging problems in speech signal processing. Speaker representa…

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…