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20242026
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cs.SD2026

Evaluating and Rewarding LALMs for Expressive Role-Play TTS via Mean Continuation Log-Probability

Yong Ren, Jingbei Li, Haiyang Sun +6

Recent advances in Large Audio Language Models (LALMs) have extended Text-to-Speech (TTS) to interactive role-play scenarios, which demand high expressiveness and strict adherence…

cs.SD2026

OV-InstructTTS: Towards Open-Vocabulary Instruct Text-to-Speech

Yong Ren, Jiangyan Yi, Jianhua Tao +5

Instruct Text-to-Speech (InstructTTS) leverages natural language descriptions as style prompts to guide speech synthesis. However, existing InstructTTS methods mainly rely on a dir…

cs.SD2025

ALLM4ADD: Unlocking the Capabilities of Audio Large Language Models for Audio Deepfake Detection

Hao Gu, Jiangyan Yi, Chenglong Wang +6

Audio deepfake detection (ADD) has grown increasingly important due to the rise of high-fidelity audio generative models and their potential for misuse. Given that audio large lang…

cs.SD2025

Manipulated Regions Localization For Partially Deepfake Audio: A Survey

Jiayi He, Jiangyan Yi, Jianhua Tao +2

With the development of audio deepfake techniques, attacks with partially deepfake audio are beginning to rise. Compared to fully deepfake, it is much harder to be identified by th…

cs.SD2024

Region-Based Optimization in Continual Learning for Audio Deepfake Detection

Yujie Chen, Jiangyan Yi, Cunhang Fan +10

Rapid advancements in speech synthesis and voice conversion bring convenience but also new security risks, creating an urgent need for effective audio deepfake detection. Although…

cs.SD2024

Reject Threshold Adaptation for Open-Set Model Attribution of Deepfake Audio

Xinrui Yan, Jiangyan Yi, Jianhua Tao +6

Open environment oriented open set model attribution of deepfake audio is an emerging research topic, aiming to identify the generation models of deepfake audio. Most previous work…