Article

Analyzing wav2vec embedding in Parkinson’s disease speech: A study on cross-database classification and regression tasks

2024-04-12

Abstract excerpt

Advancements in deep learning speech representations have facilitated the effective use of extensive datasets comprised of unlabeled speech signals, and have achieved success in modeling tasks associated with Parkinson’s disease (PD) with minimal annotated data. This study focuses on PD non-fine-tuned wav2vec 1.0 architecture. Utilizing features derived from wav2vec embedding, we develop machine learning models ta...

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Literature Corpus work: a8a116cf-e0ab-5bcb-9077-7113ce90bf8d
DOI: 10.1101/2024.04.10.24305599

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