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Related papers: PolySLGen: Online Multimodal Speaking-Listening Re…

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Effective human behavior modeling is critical for successful human-robot interaction. Current state-of-the-art approaches for predicting listening head behavior during dyadic conversations employ continuous-to-discrete representations,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Tri Tung Nguyen Nguyen , Quang Tien Dam , Dinh Tuan Tran , Joo-Ho Lee

This work aims to create a multimodal AI system that chats with humans and shares relevant photos. While earlier works were limited to dialogues about specific objects or scenes within images, recent works have incorporated images into…

Computation and Language · Computer Science 2023-05-08 Min Young Lee

In this paper, we propose a talking face generation method that takes an audio signal as input and a short target video clip as reference, and synthesizes a photo-realistic video of the target face with natural lip motions, head poses, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Chenxu Zhang , Yifan Zhao , Yifei Huang , Ming Zeng , Saifeng Ni , Madhukar Budagavi , Xiaohu Guo

While previous audio-driven talking head generation (THG) methods generate head poses from driving audio, the generated poses or lips cannot match the audio well or are not editable. In this study, we propose \textbf{PoseTalk}, a THG system…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Jun Ling , Yiwen Wang , Han Xue , Rong Xie , Li Song

Multi-modal large language models have garnered significant interest recently. Though, most of the works focus on vision-language multi-modal models providing strong capabilities in following vision-and-language instructions. However, we…

Computation and Language · Computer Science 2023-09-19 Yu Shu , Siwei Dong , Guangyao Chen , Wenhao Huang , Ruihua Zhang , Daochen Shi , Qiqi Xiang , Yemin Shi

Generative models have advanced rapidly, enabling impressive talking head generation that brings AI to life. However, most existing methods focus solely on one-way portrait animation. Even the few that support bidirectional conversational…

Audio and Speech Processing · Electrical Eng. & Systems 2025-11-25 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

This paper reports on the GENEA Challenge 2023, in which participating teams built speech-driven gesture-generation systems using the same speech and motion dataset, followed by a joint evaluation. This year's challenge provided data on…

Human-Computer Interaction · Computer Science 2023-08-25 Taras Kucherenko , Rajmund Nagy , Youngwoo Yoon , Jieyeon Woo , Teodor Nikolov , Mihail Tsakov , Gustav Eje Henter

Expressions are fundamental to conveying human emotions. With the rapid advancement of AI-generated content (AIGC), realistic and expressive 3D facial animation has become increasingly crucial. Despite recent progress in speech-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Yuxiang Mao , Zhijie Zhang , Zhiheng Zhang , Jiawei Liu , Chen Zeng , Shihong Xia

The emergence of large language models (LLMs) has revolutionized the capabilities of text comprehension and generation. Multi-modal generation attracts great attention from both the industry and academia, but there is little work on…

Information Retrieval · Computer Science 2024-04-16 Xiaoteng Shen , Rui Zhang , Xiaoyan Zhao , Jieming Zhu , Xi Xiao

Generating holistic co-speech gestures that integrate full-body motion with facial expressions suffers from semantically incoherent coordination on body motion and spatially unstable meaningless movements due to existing part-decomposed or…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Xuanmeng Sha , Liyun Zhang , Tomohiro Mashita , Naoya Chiba , Yuki Uranishi

Multimodal-driven talking face generation refers to animating a portrait with the given pose, expression, and gaze transferred from the driving image and video, or estimated from the text and audio. However, existing methods ignore the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Chao Xu , Shaoting Zhu , Junwei Zhu , Tianxin Huang , Jiangning Zhang , Ying Tai , Yong Liu

In this paper, we address the task of multimodal-to-speech generation, which aims to synthesize high-quality speech from multiple input modalities: text, video, and reference audio. This task has gained increasing attention due to its wide…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Jeongsoo Choi , Ji-Hoon Kim , Kim Sung-Bin , Tae-Hyun Oh , Joon Son Chung

Generating realistic human motions that naturally respond to both spoken language and physical objects is crucial for interactive digital experiences. Current methods, however, address speech-driven gestures or object interactions…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Sreehari Rajan , Kunal Bhosikar , Charu Sharma

Recent advancements in audio generation have been spurred by the evolution of large-scale deep learning models and expansive datasets. However, the task of video-to-audio (V2A) generation continues to be a challenge, principally because of…

Audio and Speech Processing · Electrical Eng. & Systems 2023-09-20 Xinhao Mei , Varun Nagaraja , Gael Le Lan , Zhaoheng Ni , Ernie Chang , Yangyang Shi , Vikas Chandra

This paper explores the potential of constructing an AI spoken dialogue system that "thinks how to respond" and "thinks how to speak" simultaneously, which more closely aligns with the human speech production process compared to the current…

Computation and Language · Computer Science 2023-09-21 Xinyu Zhou , Delong Chen , Yudong Chen

Turn-taking prediction is crucial for seamless interactions. This study introduces a novel, lightweight framework for accurate turn-taking prediction in triadic conversations without relying on computationally intensive methods. Unlike…

Human-Computer Interaction · Computer Science 2025-05-30 Seongsil Heo , Calvin Murdock , Michael Proulx , Christi Miller

We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length. While previous works focused on co-speech gesture or expression generation individually, the joint…

Sound · Computer Science 2024-04-09 Junming Chen , Yunfei Liu , Jianan Wang , Ailing Zeng , Yu Li , Qifeng Chen

Audio-driven co-speech human gesture generation has made remarkable advancements recently. However, most previous works only focus on single person audio-driven gesture generation. We aim at solving the problem of conversational co-speech…

Human-Computer Interaction · Computer Science 2024-01-12 Haiwei Xue , Sicheng Yang , Zhensong Zhang , Zhiyong Wu , Minglei Li , Zonghong Dai , Helen Meng

The growing prevalence of conversational voice interfaces, powered by developments in both speech and language technologies, raises important questions about their influence on human communication. While written communication can signal…

Computers and Society · Computer Science 2025-06-10 Éva Székely , Jūra Miniota , Míša , Hejná

The ability to envisage the visual of a talking face based just on hearing a voice is a unique human capability. There have been a number of works that have solved for this ability recently. We differ from these approaches by enabling a…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Ravindra Yadav , Ashish Sardana , Vinay P Namboodiri , Rajesh M Hegde