Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey
Human–robot interaction (HRI) has escalated in notability in recent years, and multimodal
communication and control strategies are necessitated to guarantee a secure, efficient, and …
communication and control strategies are necessitated to guarantee a secure, efficient, and …
Human and artificial intelligence collaboration for socially shared regulation in learning
Artificial intelligence (AI) has generated a plethora of new opportunities, potential and
challenges for understanding and supporting learning. In this paper, we position human and …
challenges for understanding and supporting learning. In this paper, we position human and …
Emoca: Emotion driven monocular face capture and animation
As 3D facial avatars become more widely used for communication, it is critical that they
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …
faithfully convey emotion. Unfortunately, the best recent methods that regress parametric 3D …
Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals
Depression stands as one of the most widespread psychological disorders and has
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
garnered increasing attention. Currently, how to effectively achieve automatic multimodal …
Uncertainty-aware label distribution learning for facial expression recognition
Despite significant progress over the past few years, ambiguity is still a key challenge in
Facial Expression Recognition (FER). It can lead to noisy and inconsistent annotation, which …
Facial Expression Recognition (FER). It can lead to noisy and inconsistent annotation, which …
Hybrid curriculum learning for emotion recognition in conversation
Emotion recognition in conversation (ERC) aims to detect the emotion label for each
utterance. Motivated by recent studies which have proven that feeding training examples in …
utterance. Motivated by recent studies which have proven that feeding training examples in …
An EEG data processing approach for emotion recognition
As the most direct way to measure the true emotional states of humans, EEG-based emotion
recognition has been widely used in affective computing applications. In this paper, we aim …
recognition has been widely used in affective computing applications. In this paper, we aim …
A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party Conversations
Abstract Multimodal Emotion Recognition in Multiparty Conversations (MERMC) has
recently attracted considerable attention. Due to the complexity of visual scenes in multi …
recently attracted considerable attention. Due to the complexity of visual scenes in multi …
From speaker to dubber: movie dubbing with prosody and duration consistency learning
Movie Dubbing aims to convert scripts into speeches that align with the given movie clip in
both temporal and emotional aspects while preserving the vocal timbre of one brief …
both temporal and emotional aspects while preserving the vocal timbre of one brief …
Learning to dub movies via hierarchical prosody models
Given a piece of text, a video clip and a reference audio, the movie dubbing (also known as
visual voice clone, V2C) task aims to generate speeches that match the speaker's emotion …
visual voice clone, V2C) task aims to generate speeches that match the speaker's emotion …