activity
20242026
most citedEnvSDD: Benchmarking Environmental Sound Deepfake Detection

6 citations · 9 across the 18 of their papers we have counts for

collaborators
Showing eess.ASShow all

12 papers · 1 filter

eess.AS2025

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…

eess.AS2025

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…

eess.AS2025

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…

eess.AS2024

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…

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…