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20242026
most citedLeveraging Prompt Learning and Pause Encoding for Alzheimer's Disease Detection

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2026

End-to-End Markov State Sequence Learning for Auditory Attention Decoding

Yushan Yashengjiang, Jie Zhang, Miao Sun +3

Auditory attention decoding (AAD) identifies the speaker a listener attends to from neural responses like electroencephalography (EEG), making it a key algorithm in neuro-steered h…

eess.AS2025

Leveraging Cascaded Binary Classification and Multimodal Fusion for Dementia Detection through Spontaneous Speech

Yin-Long Liu, Yuanchao Li, Rui Feng +7

This paper presents our submission to the PROCESS Challenge 2025, focusing on spontaneous speech analysis for early dementia detection. For the three-class classification task (Hea…

cs.SD2025

Decoding Speaker-Normalized Pitch from EEG for Mandarin Perception

Jiaxin Chen, Yiming Wang, Ziyu Zhang +6

The same speech content produced by different speakers exhibits significant differences in pitch contour, yet listeners' semantic perception remains unaffected. This phenomenon may…

eess.AS2025★ 1 cited

Beyond Manual Transcripts: The Potential of Automated Speech Recognition Errors in Improving Alzheimer's Disease Detection

Yin-Long Liu, Rui Feng, Jia-Xin Chen +3

Recent breakthroughs in Automatic Speech Recognition (ASR) have enabled fully automated Alzheimer's Disease (AD) detection using ASR transcripts. Nonetheless, the impact of ASR err…

eess.AS2024★ 4 cited

Leveraging Prompt Learning and Pause Encoding for Alzheimer's Disease Detection

Yin-Long Liu, Rui Feng, Jia-Hong Yuan +1

Compared to other clinical screening techniques, speech-and-language-based automated Alzheimer's disease (AD) detection methods are characterized by their non-invasiveness, cost-ef…