Sirvi Autor "Krass, Aleksis" järgi

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Parkinsoni tõve tuvastamine eestikeelsete hääleklippide analüüsi abil kasutades masinõppe meetodeid
(Tartu Ülikool, 2025) Krass, Aleksis; Järve, Joonas, juhendaja; Taba, Pille, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
This Bachelor’s thesis investigates the applicability of machine learning methods for Parkinson’s Disease (PD) detection using Estonian voice clips. The research focuses on three main questions: firstly, evaluating the generalizability of an acoustic feature-based model trained on the Spanish PC-GITA dataset to Estonian data; secondly, examining whether combining Spanish and Estonian data during training improves model performance; and thirdly, testing the direct applicability of a state-of-the-art self-supervised learning (SSL) based WavLM Base model, fine-tuned elsewhere, on Estonian data. The results indicate that the direct cross-lingual transferability of acoustic feature-based models is limited, but combining datasets significantly improves performance up to 0.7893. The direct application of a pre-fine-tuned SSL model on short Estonian audio segments without further adaptation was not successful. The thesis highlights the need for language-specific adaptation and the use of multilingual datasets in voice-based PD detection.