103 citations · 232 across the 18 of their papers we have counts for
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Bilingual Dual-Head Deep Model for Parkinson's Disease Detection from Speech
Moreno La Quatra, Juan Rafael Orozco-Arroyave, Marco Sabato Siniscalchi
This work aims to tackle the Parkinson's disease (PD) detection problem from the speech signal in a bilingual setting by proposing an ad-hoc dual-head deep neural architecture for…
Exploiting Foundation Models and Speech Enhancement for Parkinson's Disease Detection from Speech in Real-World Operative Conditions
Moreno La Quatra, Maria Francesca Turco, Torbjørn Svendsen +3
This work is concerned with devising a robust Parkinson's (PD) disease detector from speech in real-world operating conditions using (i) foundational models, and (ii) speech enhanc…
Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages
Soroosh Tayebi Arasteh, Cristian David Rios-Urrego, Elmar Noeth +4
Parkinson's disease (PD) is a neurological disorder impacting a person's speech. Among automatic PD assessment methods, deep learning models have gained particular interest. Recent…
Representation Learning Strategies to Model Pathological Speech: Effect of Multiple Spectral Resolutions
Gabriel Figueiredo Miller, Juan Camilo Vásquez-Correa, Juan Rafael Orozco-Arroyave +1
This paper considers a representation learning strategy to model speech signals from patients with Parkinson's disease and cleft lip and palate. In particular, it compares differen…
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling
Philipp Klumpp, Tomás Arias-Vergara, Paula Andrea Pérez-Toro +2
Current state of the art acoustic models can easily comprise more than 100 million parameters. This growing complexity demands larger training datasets to maintain a decent general…
The Phonetic Footprint of Parkinson's Disease
Philipp Klumpp, Tomás Arias-Vergara, Juan Camilo Vásquez-Correa +4
As one of the most prevalent neurodegenerative disorders, Parkinson's disease (PD) has a significant impact on the fine motor skills of patients. The complex interplay of different…
Comparison of user models based on GMM-UBM and i-vectors for speech, handwriting, and gait assessment of Parkinson's disease patients
J. C. Vasquez-Correa, T. Bocklet, J. R. Orozco-Arroyave +1
Parkinson's disease is a neurodegenerative disorder characterized by the presence of different motor impairments. Information from speech, handwriting, and gait signals have been c…