The paper introduces Noise-Aware BEATs (NABEATs), a noise-aware audio self-supervised learning framework that estimates clean BEATs representations from noisy audio signals using an auxiliary referenc…

This paper proposes the RFFBCGA algorithm, a random Fourier feature based bias-compensated filter that mitigates input noise interference and enhances robustness in nonlinear adaptive filtering.

This paper presents a companding ADC architecture for digital MEMS microphones that mitigates boundary artifacts using a VCO-based ADC and a multi-rate frequency-to-digital converter, achieving a dyna…

This paper shows that under standard assumptions, there is no polynomial-time verifier for exact verification of ReLU networks in an adversarial smoothed model.

The paper formally proves a theorem regarding adversarial noise amplification and proposes a novel, lightweight detection mechanism that uses this enhanced signal for robust adversarial defense.

This paper tests the impact of acoustic factors on voice control systems and introduces a Dual-Form Signal to Noise Ratio to decouple source stealth from attack efficacy.

This paper investigates the necessity of interaction for order-optimal 1-bit mean estimation in nonparametric finite-moment classes.

This paper proposes a learning-based method for sound field estimation using a physics-constrained neural kernel with a source-position-dependent INR for directional weighting function.

This paper proposes a framework for measuring stadium noise levels with spatially distributed acoustic measurements, criticizing the lack of standardization in current record-breaking claims.

The paper introduces DECKER, a domain-invariant framework that significantly improves cross-keyboard keystroke inference by normalizing device variations and leveraging linguistic context, demonstrati…

Low-Pass Flow Matching introduces a spectral bias into the flow matching process, allowing it to better model natural data by transitioning from a standard source spectrum to a frequency-decaying bias…

This paper introduces a systematic, privacy-preserving method using keystroke dynamics to robustly distinguish between human typing and automated HID injection attacks, independent of user identity.

This paper explores the possibility of using intrinsic device noise in analog neuromorphic hardware as a consolidation mechanism instead of an accuracy tax.

This paper introduces RealDESED, a new benchmark for domestic sound event detection with 5,710 recordings, precise annotations, and multi-annotator labeling.

This paper investigates the effectiveness of incorporating synthetic speech data in Automatic Speech Recognition (ASR) Systems for three Indic languages by analyzing performance gains, script sources,…

The paper proposes FOAM, an adaptive damping method that stabilizes the Shampoo optimization algorithm by dynamically controlling damping and eigendecomposition frequency, thereby reducing staleness-i…

This paper introduces Curvature-Weighted Gradient Diversity (CWGD), a geometry-aware measure for optimization noise that reduces the asymptotic optimization error floor by up to a factor of two compar…