activity
20232026
most citedADD 2023: the Second Audio Deepfake Detection Challenge

20 citations · 34 across the 15 of their papers we have counts for

collaborators

15 papers

cs.MA2026

TACO: Tool-Augmented Credit Optimization for Agentic Tool Use

Mingkuan Feng, Jinyang Wu, Hao Gu +5

Agentic multimodal models perform diverse operations on an image via code and reason over the returned view, an effective paradigm for fine-grained visual question answering. Howev…

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.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.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.MM2025

Hearing from Silence: Reasoning Audio Descriptions from Silent Videos via Vision-Language Model

Yong Ren, Chenxing Li, Le Xu +7

Humans can intuitively infer sounds from silent videos, but whether multimodal large language models can perform modal-mismatch reasoning without accessing target modalities remain…

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.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…

cs.HC2024★ 1 cited

OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +13

Multimodal Emotion Recognition (MER) is a critical research area that seeks to decode human emotions from diverse data modalities. However, existing machine learning methods predom…

cs.SD2024

Utilizing Speaker Profiles for Impersonation Audio Detection

Hao Gu, JiangYan Yi, Chenglong Wang +5

Fake audio detection is an emerging active topic. A growing number of literatures have aimed to detect fake utterance, which are mostly generated by Text-to-speech (TTS) or voice c…

eess.AS2024★ 2 cited

ADD 2023: Towards Audio Deepfake Detection and Analysis in the Wild

Jiangyan Yi, Chu Yuan Zhang, Jianhua Tao +5

The growing prominence of the field of audio deepfake detection is driven by its wide range of applications, notably in protecting the public from potential fraud and other malicio…

cs.LG2024★ 2 cited

MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +15

Multimodal emotion recognition is an important research topic in artificial intelligence. Over the past few decades, researchers have made remarkable progress by increasing the dat…

cs.HC2024★ 6 cited

MERBench: A Unified Evaluation Benchmark for Multimodal Emotion Recognition

Zheng Lian, Licai Sun, Yong Ren +5

Multimodal emotion recognition plays a crucial role in enhancing user experience in human-computer interaction. Over the past few decades, researchers have proposed a series of alg…

cs.CV2023★ 3 cited

GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition

Zheng Lian, Licai Sun, Haiyang Sun +5

Recently, GPT-4 with Vision (GPT-4V) has demonstrated remarkable visual capabilities across various tasks, but its performance in emotion recognition has not been fully evaluated.…

cs.SD2023★ 20 cited

ADD 2023: the Second Audio Deepfake Detection Challenge

Jiangyan Yi, Jianhua Tao, Ruibo Fu +15

Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the…