GC-P4.12
ALS DETECTION FROM PHONATION AUDIO USING SPECTROGRAM MOSAICS AND ENSEMBLE DEEP LEARNING
Marc-André Blais, Moulay Akhloufi, Université de Moncton, Canada
Session:
GC-P4: Speech Analysis for Neurodegenerative Diseases (SAND) Poster
Track:
SP Grand Challenges
Location:
Poster Area 43
Presentation Time:
Wed, 6 May, 16:30 - 18:30
Presentation
Discussion
Resources
No resources available.
Session GC-P4
GC-P4.9: SYLLABLE-LEVEL ACOUSTIC MODELING WITH A STAGE-AWARE TRANSFORMER FOR ALS DYSARTHRIA SEVERITY ESTIMATION - ICASSP-2026 SAND CHALLENGE
Yuho Tamura, Mondher Bouazizi, Tomoaki Ohtsuki, Keio University, Japan
GC-P4.10: THE SPEECH ANALYSIS FOR NEURODEGENERATIVE DISEASES CHALLENGE
Giovanna Sannino, Ivanoe De Falco, Nadia Brancati, National Research Council of Italy (CNR), Italy; Laura Verde, University of Campania “Luigi Vanvitelli”, Italy; Maria Frucci, National Research Council of Italy (CNR), Italy; Daniel Riccio, University of Naples “Federico II”, Italy; Vincenzo Bevilacqua, Antonio Di Marino, National Research Council of Italy (CNR), Italy; Lucia Aruta, Valentina Virginia Iuzzolino, Gianmaria Senerchia, University of Naples “Federico II”, Italy; Myriam Spisto, University of Campania “Luigi Vanvitelli”, Italy; Raffaele Dubbioso, University of Naples “Federico II”, Italy
GC-P4.11: A Hierarchical Coarse-to-Fine Whisper Adaptation Framework for ALS Dysarthria Severity Estimation
Sebastian Hreško, Máté Hireš, Ján Staš, Peter Drotár, Technical University of Kosice, Slovakia
GC-P4.12: ALS DETECTION FROM PHONATION AUDIO USING SPECTROGRAM MOSAICS AND ENSEMBLE DEEP LEARNING
Marc-André Blais, Moulay Akhloufi, Université de Moncton, Canada
GC-P4.13: WAVLM-BASED FEATURE FUSION WITH METADATA FOR ALS SEVERITY PREDICTION
Insung Lee, Taeyoung Jeong, Minsu Han, Yunkyung Lee, Myoung-Wan Koo, Sogang University, Korea, Republic of
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