From the 1 of 7 linked papers with an AI index.
7 papers
Investigating Codec-Internal Latent Audio Watermarking for Neural Codec Robustness
Zi Hu, Houmin Sun, Linxi Li +4
Neural audio codecs are challenging transformations for audio watermarking because they re-encode, quantize, and resynthesize speech. This paper investigates continuous latent-spac…
Making Separation-First Multi-Stream Audio Watermarking Feasible via Joint Training
Houmin Sun, Zi Hu, Linxi Li +4
The paper introduces a joint training method that combines audio watermarking with source separation, allowing distinct watermarks to be embedded in individual stems and reliably r…
PC-Mix: Partial-Component Audio Spoofing Detection under Mixed Speech and Environmental Sound Conditions
Zhenshan Zhang, Xueping Zhang, Linxi Li +2
Recent studies on partial audio spoofing mainly focus on studio-recorded speech with temporal localization of spoofed segments. However, these studies often overlook realistic cond…
SynSFX: Multi-Model Sound Effects Synthesis Dataset for Deepfake Detection and Evaluation
Linxi Li, Yuncong Yu, Qianwei Guo +3
While audio deepfake detection has advanced significantly, representative detectors show limited generalization to synthetic sound effects. Existing environmental audio datasets su…
MultiAPI Spoof: A Multi-API Dataset and Local-Attention Network for Speech Anti-spoofing Detection
Xueping Zhang, Zhenshan Zhang, Yechen Wang +3
Existing speech anti-spoofing benchmarks rely on a narrow set of public models, creating a substantial gap from real-world scenarios in which commercial systems employ diverse, oft…
CompSpoof: A Dataset and Joint Learning Framework for Component-Level Audio Anti-spoofing Countermeasures
Xueping Zhang, Yechen Wang, Linxi Li +2
Component-level audio Spoofing (Comp-Spoof) targets a new form of audio manipulation where only specific components of a signal, such as speech or environmental sound, are forged o…