409 citations · 1.5k across the 95 of their papers we have counts for
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Detection and Evaluation of human and machine generated speech in spoofing attacks on automatic speaker verification systems
Yang Gao, Jiachen Lian, Bhiksha Raj +1
Automatic speaker verification (ASV) systems utilize the biometric information in human speech to verify the speaker's identity. The techniques used for performing speaker verifica…
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances
Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad +3
Speaker identification models are vulnerable to carefully designed adversarial perturbations of their input signals that induce misclassification. In this work, we propose a white-…
Masked Proxy Loss For Text-Independent Speaker Verification
Jiachen Lian, Aiswarya Vinod Kumar, Hira Dhamyal +2
Open-set speaker recognition can be regarded as a metric learning problem, which is to maximize inter-class variance and minimize intra-class variance. Supervised metric learning c…
Multi-Task Learning for Interpretable Weakly Labelled Sound Event Detection
Soham Deshmukh, Bhiksha Raj, Rita Singh
Weakly Labelled learning has garnered lot of attention in recent years due to its potential to scale Sound Event Detection (SED) and is formulated as Multiple Instance Learning (MI…
Exploiting Non-Linear Redundancy for Neural Model Compression
Muhammad A. Shah, Raphael Olivier, Bhiksha Raj
Deploying deep learning models, comprising of non-linear combination of millions, even billions, of parameters is challenging given the memory, power and compute constraints of the…
Exploring Optimal DNN Architecture for End-to-End Beamformers Based on Time-frequency References
Yuichiro Koyama, Bhiksha Raj
Acoustic beamformers have been widely used to enhance audio signals. Currently, the best methods are the deep neural network (DNN)-powered variants of the generalized eigenvalue an…