8 papers
AT-ADD: A Benchmark and Challenge for Robust and All-Type Audio Deepfake Detection
Yuankun Xie, Haonan Cheng, Jiayi Zhou +12
Recent audio generation models can synthesize high-fidelity speech, environmental sound, singing voice, and music, creating new risks for multimedia trust. Existing audio deepfake…
AT-ADD: All-Type Audio Deepfake Detection Challenge Summary
Yuankun Xie, Haonan Cheng, Jiayi Zhou +11
This paper summarizes the ACM Multimedia 2026 AT-ADD Grand Challenge on all-type audio deepfake detection. AT-ADD contains two tracks: robust speech deepfake detection under realis…
Leading-Silence Augmentation and Multi-Stage Synthetic Supervision for the Second MLC-SLM Challenge
Kexin Shi, Renhe Sun, Yuge Huang +4
The second Multilingual Conversational Speech Language Model (MLC-SLM) Challenge evaluates two tasks over complete, unsegmented multilingual conversations: speaker diarization and…
Natural Yet Challenging to Detect: Robust In-the-Wild TTS through EMA and Dual-Scoring Prompt Selection -- Submission for WildSpoof 2026 TTS Track
Renhe Sun, Jiayi Zhou, Haolin He +2
In this technical report, we describe our submission for the WildSpoof Challenge TTS Track: Text-to-Speech with In-the-Wild Data. We introduce F5-TTS-DPS, a model built upon the F5…
EnvTriCascade: An Environment-Aware Tri-Stage Cascaded Framework for ESDD2 2026 Challenge
Hengyan Huang, Xiaoxuan Guo, Jiayi Zhou +5
ADD in real-world scenarios has evolved from speech-only spoofing to more challenging component-level settings, where speech and environmental sounds may be independently manipulat…
Towards Explicit Acoustic Evidence Perception in Audio LLMs for Speech Deepfake Detection
Xiaoxuan Guo, Yuankun Xie, Haonan Cheng +5
Speech deepfake detection (SDD) focuses on identifying whether a given speech signal is genuine or has been synthetically generated. Existing audio large language model (LLM)-based…
Interpretable All-Type Audio Deepfake Detection with Audio LLMs via Frequency-Time Reinforcement Learning
Yuankun Xie, Xiaoxuan Guo, Jiayi Zhou +6
Recent advances in audio large language models (ALLMs) have made high-quality synthetic audio widely accessible, increasing the risk of malicious audio deepfakes across speech, env…
EnvSSLAM-FFN: Lightweight Layer-Fused System for ESDD 2026 Challenge
Xiaoxuan Guo, Hengyan Huang, Jiayi Zhou +5
Recent advances in generative audio models have enabled high-fidelity environmental sound synthesis, raising serious concerns for audio security. The ESDD 2026 Challenge therefore…