8 citations · 13 across the 11 of their papers we have counts for
11 papers
LLM-based Multimodal Personality Recognition via Facial Action Unit-Text Semantic Fusion
Tianyi Zhang, Wei Shan, Yuan Zong +2
Personality recognition in asynchronous video interviews (AVIs) has become increasingly important due to their widespread adoption in modern recruitment. Existing approaches often…
AffectSpeech: A Large-Scale Emotional Speech Dataset with Fine-Grained Textual Descriptions for Speech Emotion Captioning and Synthesis
Tianhua Qi, Wenming Zheng, Björn W. Schuller +2
Emotion is essential in spoken communication, yet most existing frameworks in speech emotion modeling rely on predefined categories or low-dimensional continuous attributes, which…
Towards Realistic Emotional Voice Conversion using Controllable Emotional Intensity
Tianhua Qi, Shiyan Wang, Cheng Lu +3
Realistic emotional voice conversion (EVC) aims to enhance emotional diversity of converted audios, making the synthesized voices more authentic and natural. To this end, we propos…
Temporal Label Hierachical Network for Compound Emotion Recognition
Sunan Li, Hailun Lian, Cheng Lu +5
The emotion recognition has attracted more attention in recent decades. Although significant progress has been made in the recognition technology of the seven basic emotions, exist…
PAVITS: Exploring Prosody-aware VITS for End-to-End Emotional Voice Conversion
Tianhua Qi, Wenming Zheng, Cheng Lu +2
In this paper, we propose Prosody-aware VITS (PAVITS) for emotional voice conversion (EVC), aiming to achieve two major objectives of EVC: high content naturalness and high emotion…
Emotion-Aware Contrastive Adaptation Network for Source-Free Cross-Corpus Speech Emotion Recognition
Yan Zhao, Jincen Wang, Cheng Lu +4
Cross-corpus speech emotion recognition (SER) aims to transfer emotional knowledge from a labeled source corpus to an unlabeled corpus. However, prior methods require access to sou…
Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition
Yong Wang, Cheng Lu, Hailun Lian +4
Swin-Transformer has demonstrated remarkable success in computer vision by leveraging its hierarchical feature representation based on Transformer. In speech signals, emotional inf…
Improving Speaker-independent Speech Emotion Recognition Using Dynamic Joint Distribution Adaptation
Cheng Lu, Yuan Zong, Hailun Lian +3
In speaker-independent speech emotion recognition, the training and testing samples are collected from diverse speakers, leading to a multi-domain shift challenge across the featur…
Towards Domain-Specific Cross-Corpus Speech Emotion Recognition Approach
Yan Zhao, Yuan Zong, Hailun Lian +3
Cross-corpus speech emotion recognition (SER) poses a challenge due to feature distribution mismatch, potentially degrading the performance of established SER methods. In this pape…
Learning to Rank Onset-Occurring-Offset Representations for Micro-Expression Recognition
Jie Zhu, Yuan Zong, Jingang Shi +3
This paper focuses on the research of micro-expression recognition (MER) and proposes a flexible and reliable deep learning method called learning to rank onset-occurring-offset re…
Layer-Adapted Implicit Distribution Alignment Networks for Cross-Corpus Speech Emotion Recognition
Yan Zhao, Yuan Zong, Jincen Wang +4
In this paper, we propose a new unsupervised domain adaptation (DA) method called layer-adapted implicit distribution alignment networks (LIDAN) to address the challenge of cross-c…