7 citations · 18 across the 31 of their papers we have counts for
13 papers · 1 filter
What Do Deepfake Audio Detectors Hear? From Self-Supervised Models to Audio LLMs
Wanying Ge, Xin Wang, Junichi Yamagishi
Real-world audio recordings for deepfake detection rarely consist solely of speech; they often are mixtures of speech and background events that themselves may also be synthetic. W…
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…
Combining Self-Embedding Audio Watermarking with Ultra-Low-Bitrate Neural Codecs
Yigitcan Özer, Xin Wang, Zhe Zhang +1
Partial manipulation of speech recordings, where only localized segments of an utterance are altered, poses a significant challenge for content integrity verification, as reliable…
A Training-Free Proactive Defense Against Partial Speech Manipulation via Self-Embedding Steganography
Yigitcan Özer, Zhe Zhang, Wanying Ge +2
Partial deepfake speech, where only limited segments of an utterance are synthesized or manipulated, poses a significant challenge to existing deepfake detection systems. As the pr…
Toward Interpretable Speech Deepfake Detection using Artifact-Specific Experts and Calibrated Detection Scores
Viola Negroni, Xin Wang, Wanying Ge +3
In this work, we propose an interpretable framework for speech deepfake detection based on artifact-specific expert models. Rather than relying on black-box decisions, the framewor…
Self Voice Conversion as an Attack against Neural Audio Watermarking
Yigitcan Özer, Wanying Ge, Zhe Zhang +2
Audio watermarking embeds auxiliary information into speech while maintaining speaker identity, linguistic content, and perceptual quality. Although recent advances in neural and d…
Can External Sources Help the Knowledge Cut-off Issues in Audio Deepfake Detection?
Xuechen Liu, Xin Wang, Junichi Yamagishi +1
In conventional deepfake audio detection pipelines, inference and evaluation are typically conducted using standalone, parameterized models trained exclusively on a fixed dataset.…
LENS-DF: Deepfake Detection and Temporal Localization for Long-Form Noisy Speech
Xuechen Liu, Wanying Ge, Xin Wang +1
This study introduces LENS-DF, a novel and comprehensive recipe for training and evaluating audio deepfake detection and temporal localization under complicated and realistic audio…
MIDI-VALLE: Improving Expressive Piano Performance Synthesis Through Neural Codec Language Modelling
Jingjing Tang, Xin Wang, Zhe Zhang +3
Generating expressive audio performances from music scores requires models to capture both instrument acoustics and human interpretation. Traditional music performance synthesis pi…
Towards An Integrated Approach for Expressive Piano Performance Synthesis from Music Scores
Jingjing Tang, Erica Cooper, Xin Wang +2
This paper presents an integrated system that transforms symbolic music scores into expressive piano performance audio. By combining a Transformer-based Expressive Performance Rend…
A Preliminary Case Study on Long-Form In-the-Wild Audio Spoofing Detection
Xuechen Liu, Xin Wang, Junichi Yamagishi
Audio spoofing detection has become increasingly important due to the rise in real-world cases. Current spoofing detectors, referred to as spoofing countermeasures (CM), are mainly…
DDSP-based Neural Waveform Synthesis of Polyphonic Guitar Performance from String-wise MIDI Input
Nicolas Jonason, Xin Wang, Erica Cooper +3
We explore the use of neural synthesis for acoustic guitar from string-wise MIDI input. We propose four different systems and compare them with both objective metrics and subjectiv…
SynVox2: Towards a privacy-friendly VoxCeleb2 dataset
Xiaoxiao Miao, Xin Wang, Erica Cooper +5
The success of deep learning in speaker recognition relies heavily on the use of large datasets. However, the data-hungry nature of deep learning methods has already being question…