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Ranking Pretrained Speech Embeddings in Parkinson’s Disease Detection: Does Wav2Vec 2.0 Outperform its 1.0 Version Across Speech Modes and Languages?

2025-01-31

Abstract excerpt

Speech and language technologies are effective tools for identifying the distinct speech changes associated with Parkinson’s disease (PD), enabling earlier and more accurate diagnosis. Recent advancements in self-supervised speech pretraining, particularly with Wav2Vec models, have demonstrated superior performance over traditional feature extraction methods. While Wav2Vec 2.0 has been successfully utilized for PD...

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Literature Corpus work: 7a704cf5-eac7-5af5-a2bc-5932d716290f
DOI: 10.1101/2025.01.29.25321319

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