7 papers
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…
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…
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…
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…
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…
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…