activity
20232025
most citedEnvSDD: Benchmarking Environmental Sound Deepfake Detection

6 citations · 14 across the 13 of their papers we have counts for

collaborators

13 papers

cs.SD2025

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…

cs.SD2025

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…

cs.SD2025

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…

cs.SD2025★ 6 cited

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…

eess.AS2024

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…

eess.AS2024

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…

eess.AS2024★ 1 cited

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…

eess.AS2024

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…

eess.AS2024★ 5 cited

Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift

Jisheng Bai, Mou Wang, Haohe Liu +11

Acoustic scene classification (ASC) is a crucial research problem in computational auditory scene analysis, and it aims to recognize the unique acoustic characteristics of an envir…

eess.AS2024

Sub-band and Full-band Interactive U-Net with DPRNN for Demixing Cross-talk Stereo Music

Han Yin, Mou Wang, Jisheng Bai +3

This paper presents a detailed description of our proposed methods for the ICASSP 2024 Cadenza Challenge. Experimental results show that the proposed system can achieve better perf…

eess.AS2023★ 1 cited

Interactive Dual-Conformer with Scene-Inspired Mask for Soft Sound Event Detection

Han Yin, Jisheng Bai, Mou Wang +3

Traditional binary hard labels for sound event detection (SED) lack details about the complexity and variability of sound event distributions. Recently, a novel annotation workflow…

eess.AS2023★ 1 cited

AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning

Jisheng Bai, Han Yin, Mou Wang +4

Previous studies in automated audio captioning have faced difficulties in accurately capturing the complete temporal details of acoustic scenes and events within long audio sequenc…

eess.AS2023

Convolutional Recurrent Neural Network with Attention for 3D Speech Enhancement

Han Yin, Jisheng Bai, Mou Wang +3

3D speech enhancement can effectively improve the auditory experience and plays a crucial role in augmented reality technology. However, traditional convolutional-based speech enha…