activity
20242026
most citedTyee: A Unified, Modular, and Fully-Integrated Configurable Toolkit for Intelligent Physiological Health Care

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning

Tao Zhou, Jing Han, Lingyu Shu +1

Self-supervised foundation models have recently shown strong potential for electroencephalogram (EEG)-based analysis. However, existing approaches struggle to capture the inherentl…

cs.SD2025

AudioFab: Building A General and Intelligent Audio Factory through Tool Learning

Cheng Zhu, Jing Han, Qianshuai Xue +3

Currently, artificial intelligence is profoundly transforming the audio domain; however, numerous advanced algorithms and tools remain fragmented, lacking a unified and efficient f…

cs.CL2025★ 1 cited

Structured Prompting and LLM Ensembling for Multimodal Conversational Aspect-based Sentiment Analysis

Zhiqiang Gao, Shihao Gao, Zixing Zhang +3

Understanding sentiment in multimodal conversations is a complex yet crucial challenge toward building emotionally intelligent AI systems. The Multimodal Conversational Aspect-base…

cs.AI2025★ 1 cited

Tyee: A Unified, Modular, and Fully-Integrated Configurable Toolkit for Intelligent Physiological Health Care

Tao Zhou, Lingyu Shu, Zixing Zhang +1

Deep learning has shown great promise in physiological signal analysis, yet its progress is hindered by heterogeneous data formats, inconsistent preprocessing strategies, fragmente…

cs.SD2025

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…

cs.CL2025

DEBATE: A Dataset for Disentangling Textual Ambiguity in Mandarin Through Speech

Haotian Guo, Jing Han, Yongfeng Tu +5

Despite extensive research on textual and visual disambiguation, disambiguation through speech (DTS) remains underexplored. This is largely due to the lack of high-quality datasets…

cs.SD2024

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…

eess.AS2024

Semi-Supervised Cognitive State Classification from Speech with Multi-View Pseudo-Labeling

Yuanchao Li, Zixing Zhang, Jing Han +2

The lack of labeled data is a common challenge in speech classification tasks, particularly those requiring extensive subjective assessment, such as cognitive state classification.…