Prohlížení Publikační činnost ČVUT dle autora "Klempíř O."
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Analyzing Wav2Vec 1.0 Embeddings for Cross-Database Parkinson’s Disease Detection and Speech Features Extraction
Autor: Klempíř O.; Krupička R.
(MDPI AG, 2024)Advancements in deep learning speech representations have facilitated the effective use of extensive unlabeled speech datasets for Parkinson’s disease (PD) modeling with minimal annotated data. This study employs the ... -
Assessing Speech Intelligibility and Severity Level in Parkinson's Disease Using Wav2Vec 2.0
Autor: Smolík T.; Krupička R.; Klempíř O.
(IEEE, 2024)Parkinson's disease (PD) is characterized by profound speech and intelligibility impairments. This paper investigates the potential of Wav2Vec 2.0, a pre-trained speech transformer-based model, in assessing speech ... -
Evaluating the Performance of wav2vec Embedding for Parkinson's Disease Detection
Autor: Klempíř O.; Příhoda D.; Krupička R.
(Institute of Measurement Science of the SAS, 2023)Speech is one of the most serious manifestations of Parkinson's disease (PD). Sophisticated language/speech models have already demonstrated impressive performance on a variety of tasks, including classification. By analysing ...