Communication Dans Un Congrès Année : 2025

VoiceTransformer pour la détection précoce des maladies neurodégénératives

Résumé

This work explores the use of attention-based models (Transformers) for automatic feature extraction from vocal data to detect neurodegenerative diseases. These models capture long-term dependencies in speech sequences, making them suitable for identifying early signs of these pathologies. By fine-tuning pre-trained encoders on patient data, the study assesses performance compared to traditional acoustic descriptors and machine learning models. The findings highlight the potential of attention-based approaches for enhancing non-invasive diagnostic systems using voice analysis.

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Dates et versions

hal-05295003 , version 1 (02-10-2025)

Identifiants

  • HAL Id : hal-05295003 , version 1

Citer

Ahmad Tay, Mohamed Djallel Dilmi, Faten Chaieb. VoiceTransformer pour la détection précoce des maladies neurodégénératives. Extraction et Gestion des Connaissances, EGC’2025, Jan 2025, Strasbourg, France. ⟨hal-05295003⟩
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