1 citations · 2 across the 7 of their papers we have counts for
8 papers
Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection
Hangbin Yu, Yudong Yang, Rongfeng Su +2
Automatic depression detection using speech signals with acoustic and textual modalities is a promising approach for early diagnosis. Depression-related patterns exhibit sparsity i…
UTI-LLM: A Personalized Articulatory-Speech Therapy Assistance System Based on Multimodal Large Language Model
Yudong Yang, Xiaokang Liu, Shaofeng zhao +3
Speech therapy is essential for rehabilitating speech disorders caused by neurological impairments such as stroke. However, traditional manual and computer-assisted systems are lim…
Magnitude and Phase-based Feature Fusion Using Co-attention Mechanism for Speaker recognition
Rongfeng Su, Mengjie Du, Xiaokang Liu +2
Phase-based features related to vocal source characteristics can be incorporated into magnitude-based speaker recognition systems to improve the system performance. However, tradit…
Investigating Acoustic-Textual Emotional Inconsistency Information for Automatic Depression Detection
Rongfeng Su, Changqing Xu, Xinyi Wu +4
Previous studies have demonstrated that emotional features from a single acoustic sentiment label can enhance depression diagnosis accuracy. Additionally, according to the Emotion…
Automatic Assessment of Dysarthria Using Audio-visual Vowel Graph Attention Network
Xiaokang Liu, Xiaoxia Du, Juan Liu +7
Automatic assessment of dysarthria remains a highly challenging task due to high variability in acoustic signals and the limited data. Currently, research on the automatic assessme…
An Audio-textual Diffusion Model For Converting Speech Signals Into Ultrasound Tongue Imaging Data
Yudong Yang, Rongfeng Su, Xiaokang Liu +2
Acoustic-to-articulatory inversion (AAI) is to convert audio into articulator movements, such as ultrasound tongue imaging (UTI) data. An issue of existing AAI methods is only usin…
On-the-Fly Feature Based Rapid Speaker Adaptation for Dysarthric and Elderly Speech Recognition
Mengzhe Geng, Xurong Xie, Rongfeng Su +7
Accurate recognition of dysarthric and elderly speech remain challenging tasks to date. Speaker-level heterogeneity attributed to accent or gender, when aggregated with age and spe…
A Multi-level Acoustic Feature Extraction Framework for Transformer Based End-to-End Speech Recognition
Jin Li, Rongfeng Su, Xurong Xie +2
Transformer based end-to-end modelling approaches with multiple stream inputs have been achieved great success in various automatic speech recognition (ASR) tasks. An important iss…