2 citations · 3 across the 12 of their papers we have counts for
12 papers
Textual Acoustic Grounding for Generalizable LLM-Based Deepfake Voice Detection
Yassine El Kheir, Xin Wang, Wanqing Ge +3
Deepfake voice detection suffers from poor generalization across unseen domains. While Audio Large Language Models (ALLMs) show promise, the modality gap between continuous audio e…
Evidence Subspace Projection: Measuring How Much Evidence Explains Deepfake Detection in Self-Supervised Speech Models
Yixuan Xiao, Cheng-Wei Lin, Xin Wang +5
Self-supervised learning (SSL) models are widely used as feature extractors for state-of-the-art audio deepfake detection, but it remains unclear how to directly and quantitatively…
DFKI-Speech System for WildSpoof Challenge: A robust framework for SASV In-the-Wild
Arnab Das, Yassine El Kheir, Enes Erdem Erdogan +3
This paper presents the DFKI-Speech system developed for the WildSpoof Challenge under the Spoofing aware Automatic Speaker Verification (SASV) track. We propose a robust SASV fram…
A Parameter-Efficient Multi-Scale Convolutional Adapter for Synthetic Speech Detection
Yassine El Kheir, Fabian Ritter-Guttierez, Arnab Das +2
Recent synthetic speech detection models typically adapt a pre-trained SSL model via finetuning, which is computationally demanding. Parameter-Efficient Fine-Tuning (PEFT) offers a…
Generalizable Audio Spoofing Detection using Non-Semantic Representations
Arnab Das, Yassine El Kheir, Carlos Franzreb +3
Rapid advancements in generative modeling have made synthetic audio generation easy, making speech-based services vulnerable to spoofing attacks. Consequently, there is a dire need…
Two Views, One Truth: Spectral and Self-Supervised Features Fusion for Robust Speech Deepfake Detection
Yassine El Kheir, Arnab Das, Enes Erdem Erdogan +3
Recent advances in synthetic speech have made audio deepfakes increasingly realistic, posing significant security risks. Existing detection methods that rely on a single modality,…