6 citations · 9 across the 18 of their papers we have counts for
18 papers
A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook
Kaiwen Luo, Zhenhong Zhou, Leyan Wang +32
Advances in Large Language Models (LLMs) have paved the way for Multimodal Large Language Models (MLLMs). Among these, Large Audio Language Models (LALMs) are essential for realizi…
ESDD2: Environment-Aware Speech and Sound Deepfake Detection Challenge Evaluation Plan
Xueping Zhang, Han Yin, Yang Xiao +4
Audio recorded in real-world environments often contains a mixture of foreground speech and background environmental sounds. With rapid advances in text-to-speech, voice conversion…
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…
Multilingual Source Tracing of Speech Deepfakes: A First Benchmark
Xi Xuan, Yang Xiao, Rohan Kumar Das +1
Recent progress in generative AI has made it increasingly easy to create natural-sounding deepfake speech from just a few seconds of audio. While these tools support helpful applic…
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…
RawTFNet: A Lightweight CNN Architecture for Speech Anti-spoofing
Yang Xiao, Ting Dang, Rohan Kumar Das
Automatic speaker verification (ASV) systems are often affected by spoofing attacks. Recent transformer-based models have improved anti-spoofing performance by learning strong feat…
Listen, Analyze, and Adapt to Learn New Attacks: An Exemplar-Free Class Incremental Learning Method for Audio Deepfake Source Tracing
Yang Xiao, Rohan Kumar Das
As deepfake speech becomes common and hard to detect, it is vital to trace its source. Recent work on audio deepfake source tracing (ST) aims to find the origins of synthetic or ma…
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…
XLSR-Mamba: A Dual-Column Bidirectional State Space Model for Spoofing Attack Detection
Yang Xiao, Rohan Kumar Das
Transformers and their variants have achieved great success in speech processing. However, their multi-head self-attention mechanism is computationally expensive. Therefore, one no…
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…
TF-Mamba: A Time-Frequency Network for Sound Source Localization
Yang Xiao, Rohan Kumar Das
Sound source localization (SSL) determines the position of sound sources using multi-channel audio data. It is commonly used to improve speech enhancement and separation. Extractin…
Where's That Voice Coming? Continual Learning for Sound Source Localization
Yang Xiao, Rohan Kumar Das
Sound source localization (SSL) is essential for many speech-processing applications. Deep learning models have achieved high performance, but often fail when the training and infe…
UCIL: An Unsupervised Class Incremental Learning Approach for Sound Event Detection
Yang Xiao, Rohan Kumar Das
This work explores class-incremental learning (CIL) for sound event detection (SED), advancing adaptability towards real-world scenarios. CIL's success in domains like computer vis…
WildDESED: An LLM-Powered Dataset for Wild Domestic Environment Sound Event Detection System
Yang Xiao, Rohan Kumar Das
This work aims to advance sound event detection (SED) research by presenting a new large language model (LLM)-powered dataset namely wild domestic environment sound event detection…
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…
Dual Knowledge Distillation for Efficient Sound Event Detection
Yang Xiao, Rohan Kumar Das
Sound event detection (SED) is essential for recognizing specific sounds and their temporal locations within acoustic signals. This becomes challenging particularly for on-device a…