1 citations · 1 across the 8 of their papers we have counts for
8 papers
LLM-Anchored Paralinguistic Enrichment for Alzheimer's Disease Detection
Xiao Wei, Yuqin Lin, Yaru Cao +6
Speech-based automatic detection of Alzheimer's disease (AD) provides a non-invasive and scalable approach to early cognitive screening. AD affects both lexical-semantic organizati…
Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection
Jinyu Li, Xiao Wei, Bin Wen +5
Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in patholo…
Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech
Xiao Wei, Bin Wen, Yuqin Lin +5
Early diagnosis of Alzheimer's Disease (AD) is crucial for delaying its progression. While AI-based speech detection is non-invasive and cost-effective, it faces a critical data ef…
Integration of Old and New Knowledge for Generalized Intent Discovery: A Consistency-driven Prototype-Prompting Framework
Xiao Wei, Xiaobao Wang, Ning Zhuang +3
Intent detection aims to identify user intents from natural language inputs, where supervised methods rely heavily on labeled in-domain (IND) data and struggle with out-of-domain (…
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective
Di Jin, Jingyi Cao, Xiaobao Wang +4
Graph anomaly detection aims to identify unusual patterns in graph-based data, with wide applications in fields such as web security and financial fraud detection. Existing methods…
Enriching Multimodal Sentiment Analysis through Textual Emotional Descriptions of Visual-Audio Content
Sheng Wu, Xiaobao Wang, Longbiao Wang +2
Multimodal Sentiment Analysis (MSA) stands as a critical research frontier, seeking to comprehensively unravel human emotions by amalgamating text, audio, and visual data. Yet, dis…
AIMDiT: Modality Augmentation and Interaction via Multimodal Dimension Transformation for Emotion Recognition in Conversations
Sheng Wu, Jiaxing Liu, Longbiao Wang +3
Emotion Recognition in Conversations (ERC) is a popular task in natural language processing, which aims to recognize the emotional state of the speaker in conversations. While curr…
An Initial Investigation of Language Adaptation for TTS Systems under Low-resource Scenarios
Cheng Gong, Erica Cooper, Xin Wang +9
Self-supervised learning (SSL) representations from massively multilingual models offer a promising solution for low-resource language speech tasks. Despite advancements, language…