September 2026

Current research on Audio Deepfake Detection (ADD) mainly relies on centralized training paradigms, while paying limited attention to privacy preservation under data localization regulations or user-c

Although front-end speech enhancement can improve automatic speech recognition (ASR) robustness, its practical deployment under frozen recognizers is often limited by within-block sequential dependenc

Controlled multichannel room impulse response (RIR) simulation supports the analysis and evaluation of coherence-sensitive microphone-array methods under explicitly stated modeling assumptions. Two la

Sound field estimation with moving microphones can increase flexibility, decrease measurement time, and reduce equipment constraints compared to using stationary microphones. In this paper a kernel ri

Audio-visual Sound Event Localization and Detection with Source Distance Estimation (AV 3D SELD) is designed to use synchronized audio-visual streams to simultaneously identify event categories, 3D sp

Voice Activity Detection (VAD) is a fundamental component that supports a wide range of audio/speech processing applications. Numerous studies have addressed VAD using a single microphone or a compact

Speech deepfake detection (SDD) is essential for maintaining trust in voice-driven technologies and digital media. Although recent SDD systems increasingly rely on self-supervised learning (SSL) repre

Self-supervised audio models are typically pre-trained on large collections of real-world recordings, and the resulting representations may be shaped by the acoustic coverage, recording conditions, an

While large language models (LLMs) have achieved impressive gains in commonsense reasoning, they often fall into “associative shortcuts,” failing to distinguish correct answers from plausible but cons

In machine reading comprehension (MRC) tasks that involve complex logical reasoning, graph structures are often regarded as a more suitable representation paradigm than plain text sequences, owing to