5 papers
Foundation Model-based Evaluation of Neuropsychiatric Disorders: A Lifespan-Inclusive, Multi-Modal, and Multi-Lingual Study
Zhongren Dong, Haotian Guo, Weixiang Xu +2
Neuropsychiatric disorders, such as Alzheimer's disease (AD), depression, and autism spectrum disorder (ASD), are characterized by linguistic and acoustic abnormalities, offering p…
SACodec: Asymmetric Quantization with Semantic Anchoring for Low-Bitrate High-Fidelity Neural Speech Codecs
Zhongren Dong, Bin Wang, Jing Han +4
Neural Speech Codecs face a fundamental trade-off at low bitrates: preserving acoustic fidelity often compromises semantic richness. To address this, we introduce SACodec, a novel…
ParaLBench: A Large-Scale Benchmark for Computational Paralinguistics over Acoustic Foundation Models
Zixing Zhang, Weixiang Xu, Zhongren Dong +5
Computational paralinguistics (ComParal) aims to develop algorithms and models to automatically detect, analyze, and interpret non-verbal information from speech communication, e.…
Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition
Zixing Zhang, Zhongren Dong, Weixiang Xu +1
With the increasing implementation of machine learning models on edge or Internet-of-Things (IoT) devices, deploying advanced models on resource-constrained IoT devices remains cha…
HAFFormer: A Hierarchical Attention-Free Framework for Alzheimer's Disease Detection From Spontaneous Speech
Zhongren Dong, Zixing Zhang, Weixiang Xu +3
Automatically detecting Alzheimer's Disease (AD) from spontaneous speech plays an important role in its early diagnosis. Recent approaches highly rely on the Transformer architectu…