arXiv Machine Learning

Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

arXiv:2608. 08976v1 Announce Type: new Abstract: Parkinson's disease (PD) is the second most common neurodegenerative disorder.

arXiv Machine Learning

Jun 9

Multi-View Speech Representation Learning for Parkinson's Disease Detection Using Context-guided Cross-modal Attention

arXiv:2606. 09271v1 Announce Type: cross Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria.

By George Theodosiou, Loukas Ilias, Dimitris Askounis

rag multimodal benchmarks

arXiv AI

Jul 21

A Benchmark for Early-stage Parkinson's Disease Detection from Speech

arXiv:2605. 14066v2 Announce Type: replace-cross Abstract: Early-stage Parkinson's disease (EarlyPD) detection from speech is clinically meaningful yet underexplored, and published results are hard to compare because studies differ in datasets, languages, tasks, evaluation protocols, and EarlyPD definitions.

By Terry Yi Zhong, Cristian Tejedor-Garcia, Khiet P. Truong, Janna Maas, Louis ten Bosch, Bastiaan R. Bloem

benchmarks

arXiv Machine Learning

Aug 11

Label-Efficient Bilateral Attention for Parkinson's Disease Screening from Wrist-Worn IMU Signals

arXiv:2604. 18372v2 Announce Type: replace Abstract: Parkinson's disease (PD) is a chronic neurodegenerative disorder.

By Meheru Zannat

efficiency

arXiv Machine Learning

Aug 4

Experience-Calibrated Contrastive Decoding for Mitigating Hallucinations in LM-Based Text-to-Speech

arXiv:2608. 00722v1 Announce Type: cross Abstract: Language model-based text-to-speech (LM-based TTS) remains vulnerable to speech hallucinations that deviate from the target text.

By Chenlin Liu, Minghui Fang, Zhonghao Bi, Zekai Su, Rong Wang, Jiqing Han

llms multimodal safety

arXiv Machine Learning

Jun 18

ActiTect: A Generalizable Machine Learning Pipeline for REM Sleep Behavior Disorder Screening through Standardized Actigraphy

arXiv:2511. 05221v3 Announce Type: replace Abstract: Isolated rapid eye movement sleep behavior disorder (iRBD) is a major prodromal marker of $\alpha$-synucleinopathies, often preceding the clinical onset of Parkinson's disease, dementia with Lewy bodies, or multiple system atrophy.

By David Bertram, Anja Ophey, Sinah R\"ottgen, Konstantin Kufer, Gereon R. Fink, Elke Kalbe, Clint Hansen, Walter Maetzler, Maximilian Kapsecker, Lara M. Reimer, Stephan Jonas, Andreas T. Damgaard, Natasha B. Bertelsen, Casper Skjaerbaek, Per Borghammer, Karolien Groenewald, Pietro-Luca Ratti, Michele T. Hu, No\'emie Moreau, Michael Sommerauer, Katarzyna Bozek

arXiv AI

Jun 16

Unifying Acoustic Features and Text with Multimodal LLMs for Neurodegenerative Screening

arXiv:2606. 14788v1 Announce Type: cross Abstract: Voice-based screening offers a scalable and non-invasive way to assess neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD), but their staging remains challenging due to the difficulty of integrating heterogeneous data.

By Qingfeng Zhang, Yuanxiong Guo, Yanmin Gong

llms rag multimodal

arXiv AI

Jul 14

Transcript-Free Lightweight Detection of Alzheimer's Disease from Spontaneous Speech Using Handcrafted MFCC-Dominant Acoustic Biomarkers

arXiv:2607. 10168v1 Announce Type: cross Abstract: It is still hard to find Alzheimer's disease (AD) early, especially when neuroimaging is expensive or tools that depend on language are not available.

By Rashin Gholijani Farahani, Azam Bastanfard

multimodal

arXiv Machine Learning

Jul 27

Physiological Signals as a Forensic Modality for Talking-Face Deepfake Detection

arXiv:2607. 21776v1 Announce Type: new Abstract: Talking-face (TF) deepfake generation synthesizes photore- alistic facial video from a static source image and an au- dio signal, producing forgeries that current image-based detectors consistently fail to identify.

By Othmane Harraq, Tamer Aldwairi

arXiv AI

Jun 19

Improving End-to-End Speech Recognition for Dysarthric Speech through In-Domain Data Augmentation

arXiv:2606. 19797v1 Announce Type: cross Abstract: Dysarthric speech recognition is crucial for facilitating effective communication among individuals with dysarthria.

By Paban Sapkota, Hemant Kumar Kathania, Sudarsana Reddy Kadiri, Shrikanth Narayanan

fine-tuning multimodal

arXiv AI

Aug 10

LSEAD: A Privacy-Preserving LLM-Based Speech Analysis Framework for Early Alzheimer's Disease Screening

arXiv:2608. 07378v1 Announce Type: cross Abstract: Early diagnosis of Alzheimer's disease (AD) is critical for enabling timely interventions that may slow disease progression and improve patient outcomes.

By Xin Wang, Yingchao Huang, Yuhan Su, Shanshan Yao, Wei Peng

llms rag benchmarks safety

arXiv Machine Learning

Jul 24

Toward Generalizable Cognitive Impairment Detection with Speech-Based Multimodal Large Language Models

arXiv:2607. 21496v1 Announce Type: cross Abstract: Cognitive impairment (CI) is a growing public health concern.

By Yingchao Huang, Xin Wang, Yuhan Su, Shanshan Yao

llms rag multimodal benchmarks safety

arXiv AI

Jun 18

Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech

arXiv:2603. 15988v3 Announce Type: replace-cross Abstract: Dysarthric speech quality assessment (DSQA) is critical for clinical diagnostics and inclusive speech technologies.

By Jaesung Bae, Xiuwen Zheng, Minje Kim, Chang D. Yoo, Mark Hasegawa-Johnson

fine-tuning multimodal benchmarks

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