activity
20222025
most citedTowards Realistic Emotional Voice Conversion using Controllable Emotional Intensity

8 citations · 15 across the 12 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

eess.AS2024★ 8 cited

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…

cs.CV2024★ 1 cited

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…

eess.AS2024

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…

cs.SD2024

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…

cs.CL2024★ 1 cited

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…

cs.SD2024★ 1 cited

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…