6 citations · 8 across the 11 of their papers we have counts for
11 papers
MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection
Yanqiu Li, Yang Xiao, Jisheng Bai +3
Recent advances in speech synthesis and audio generation have made high-fidelity acoustic forgery low-cost and difficult to attribute, enabling a realistic attack scenario in which…
The First Environmental Sound Deepfake Detection Challenge: Benchmarking Robustness, Evaluation, and Insights
Han Yin, Yang Xiao, Rohan Kumar Das +2
Recent progress in audio generation has made it increasingly easy to create highly realistic environmental soundscapes, which can be misused to produce deceptive content, such as f…
Environmental Sound Deepfake Detection Challenge: An Overview
Han Yin, Yang Xiao, Rohan Kumar Das +2
Recent progress in audio generation models has made it possible to create highly realistic and immersive soundscapes, which are now widely used in film and virtual-reality-related…
Dynamic Fusion Multimodal Network for SpeechWellness Detection
Wenqiang Sun, Han Yin, Jisheng Bai +1
Suicide is one of the leading causes of death among adolescents. Previous suicide risk prediction studies have primarily focused on either textual or acoustic information in isolat…
ESDD 2026: Environmental Sound Deepfake Detection Challenge Evaluation Plan
Han Yin, Yang Xiao, Rohan Kumar Das +2
Recent advances in audio generation systems have enabled the creation of highly realistic and immersive soundscapes, which are increasingly used in film and virtual reality. Howeve…
EnvSDD: Benchmarking Environmental Sound Deepfake Detection
Han Yin, Yang Xiao, Rohan Kumar Das +4
Audio generation systems now create very realistic soundscapes that can enhance media production, but also pose potential risks. Several studies have examined deepfakes in speech o…
Audio-Language Models for Audio-Centric Tasks: A Systematic Survey
Yi Su, Jisheng Bai, Qisheng Xu +2
Audio-Language Models (ALMs), trained on paired audio-text data, are designed to process, understand, and reason about audio-centric multimodal content. Unlike traditional supervis…
Leveraging LLM and Text-Queried Separation for Noise-Robust Sound Event Detection
Han Yin, Yang Xiao, Jisheng Bai +1
Sound Event Detection (SED) is challenging in noisy environments where overlapping sounds obscure target events. Language-queried audio source separation (LASS) aims to isolate the…
Exploring Text-Queried Sound Event Detection with Audio Source Separation
Han Yin, Jisheng Bai, Yang Xiao +6
In sound event detection (SED), overlapping sound events pose a significant challenge, as certain events can be easily masked by background noise or other events, resulting in poor…
DG-SED: Domain Generalization for Sound Event Detection with Heterogeneous Training Data
Yang Xiao, Han Yin, Jisheng Bai +1
This work explores domain generalization (DG) for sound event detection (SED), advancing adaptability to real-world scenarios. Our approach employs a mean-teacher framework with do…
FMSG-JLESS Submission for DCASE 2024 Task4 on Sound Event Detection with Heterogeneous Training Dataset and Potentially Missing Labels
Yang Xiao, Han Yin, Jisheng Bai +1
This report presents the systems developed and submitted by Fortemedia Singapore (FMSG) and Joint Laboratory of Environmental Sound Sensing (JLESS) for DCASE 2024 Task 4. The task…