7 citations · 18 across the 12 of their papers we have counts for
13 papers
AuDirector: A Self-Reflective Closed-Loop Framework for Immersive Audio Storytelling
Yiming Ren, Xuenan Xu, Ziyang Zhang +3
Despite advances in text and visual generation, creating coherent long-form audio narratives remains challenging. Existing frameworks often exhibit limitations such as mismatched c…
AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training
Qitan Lv, Hong Wang, Zhongkai Hao +5
Pre-training neural operators on diverse partial differential equation (PDE) datasets has emerged as a promising direction for building general-purpose surrogate models in scientif…
STEP: Scientific Time-Series Encoder Pretraining via Cross-Domain Distillation
Chen Zhang, Liwei Liu, Jun Tao +6
Scientific time series are central to scientific AI but are typically sparse, highly heterogeneous, and limited in scale, making unified representation learning particularly challe…
CAST-TTS: A Simple Cross-Attention Framework for Unified Timbre Control in TTS
Zihao Zheng, Wen Wu, Chao Zhang +2
Current Text-to-Speech (TTS) systems typically use separate models for speech-prompted and text-prompted timbre control. While unifying both control signals into a single model is…
Towards Paradigm-General Suicide Risk Detection via Speech LLM
Jialun Li, Weitao Jiang, Ziyun Cui +6
Suicide risk among adolescents remains a critical public health concern, and speech provides a non-invasive and scalable approach for its detection. Speech-based suicide risk asses…
Speaker Anonymisation for Speech-based Suicide Risk Detection
Ziyun Cui, Sike Jia, Yang Lin +6
Adolescent suicide is a critical global health issue, and speech provides a cost-effective modality for automatic suicide risk detection. Given the vulnerable population, protectin…
BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals
Qinfan Xiao, Ziyun Cui, Chi Zhang +6
Electroencephalography (EEG) and magnetoencephalography (MEG) measure neural activity non-invasively by capturing electromagnetic fields generated by dendritic currents. Although r…
The 1st SpeechWellness Challenge: Detecting Suicide Risk Among Adolescents
Wen Wu, Ziyun Cui, Chang Lei +6
The 1st SpeechWellness Challenge (SW1) aims to advance methods for detecting current suicide risk in adolescents using speech analysis techniques. Suicide among adolescents is a cr…
Confidence Estimation for Automatic Detection of Depression and Alzheimer's Disease Based on Clinical Interviews
Wen Wu, Chao Zhang, Philip C. Woodland
Speech-based automatic detection of Alzheimer's disease (AD) and depression has attracted increased attention. Confidence estimation is crucial for a trust-worthy automatic diagnos…
Spontaneous Speech-Based Suicide Risk Detection Using Whisper and Large Language Models
Ziyun Cui, Chang Lei, Wen Wu +5
The early detection of suicide risk is important since it enables the intervention to prevent potential suicide attempts. This paper studies the automatic detection of suicide risk…
Enhancing Zero-shot Text-to-Speech Synthesis with Human Feedback
Chen Chen, Yuchen Hu, Wen Wu +3
In recent years, text-to-speech (TTS) technology has witnessed impressive advancements, particularly with large-scale training datasets, showcasing human-level speech quality and i…
Bayesian WeakS-to-Strong from Text Classification to Generation
Ziyun Cui, Ziyang Zhang, Guangzhi Sun +2
Advances in large language models raise the question of how alignment techniques will adapt as models become increasingly complex and humans will only be able to supervise them wea…
Transferring speech-generic and depression-specific knowledge for Alzheimer's disease detection
Ziyun Cui, Wen Wu, Wei-Qiang Zhang +2
The detection of Alzheimer's disease (AD) from spontaneous speech has attracted increasing attention while the sparsity of training data remains an important issue. This paper hand…