6 papers
CoSTA: Cognitive-State-Conditioned TTS Data Augmentation Using ASR Transcripts for Alzheimer's Disease Detection
Yin-Long Liu, Yuanchao Li, Yiming Wang +8
Speech-based Alzheimer's Disease (AD) detection is constrained by scarce pathological speech data. To address this, we propose CoSTA, a Text-to-Speech (TTS)-based data augmentation…
EGGCodec: A Robust Neural Encodec Framework for EGG Reconstruction and F0 Extraction
Rui Feng, Yuang Chen, Yu Hu +2
This letter introduces EGGCodec, a robust neural Encodec framework engineered for electroglottography (EGG) signal reconstruction and F0 extraction. We propose a multi-scale freque…
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…
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…
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…
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…