The study investigates the use of neural replay simulators to improve the robustness of over-the-air adversarial attacks on Automatic Speaker Verification (ASV) systems. ASV systems, powered by deep learning, are…
Continue readingDespite the widespread use of weight decay in training deep networks, its role is not well understood. This study demonstrates how weight decay modifies the optimization dynamics in overparameterized deep…
Continue readingThis research introduces multiple physics pretraining (MPP), a new approach for physical surrogate modeling. The MPP method involves training large models to predict the dynamics of various physical systems simultaneously….
Continue readingThe article presents Soft Convex Quantization (SCQ) as a solution to the challenges of Vector Quantization (VQ) in deep learning. VQ is a technique used for extracting discrete latent representations…
Continue readingThis paper proposes a new network, the Modularized Attention-Dilated Convolutional Neural Network (MAD-CNN), specifically designed for collision detection in robots equipped with variable stiffness actuators. The authors aim to enhance…
Continue readingThis article presents research into the development of a universal speech enhancement model that can handle diverse input conditions. Existing techniques have shown strong performance but are typically designed for…
Continue readingThe article presents a novel U-Net based deep neural network architecture for denoising phonocardiogram (PCG) signals contaminated by real-world noise. The proposed architecture aims to improve the diagnosis process by…
Continue readingThe paper introduces a General Audio Source Separation (GASS) model trained with a large-scale dataset to separate different audio sources such as speech, music, and sound events. The GASS models…
Continue readingThis paper presents a study on automatic performer identification in expressive piano performances using Convolutional Neural Networks (CNNs) and expressive features. The study addresses the task of identifying virtuoso pianists,…
Continue readingThis study focuses on enhancing the accuracy of child-adult speaker classification in dyadic interactions, particularly in the context of Autism Spectrum Disorder assessments. Traditionally, this classification relies on audio modeling…
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