activity
20202026
most citedConvolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson's Disease from Speech in Three Different Languages

42 citations · 78 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2026

Multilingual Phonological Feature Recognition with Self-Supervised Speech Models

Abner Hernandez, Tomás Arias-Vergara, Daiqi Liu +2

Phonological features provide a language-general and linguistically grounded representation of speech. We present PhonoQ-2.0, a multilingual frame-level phonological feature recogn…

cs.CL2026

Adapting Self-Supervised Speech Representations for Cross-lingual Dysarthria Detection in Parkinson's Disease

Abner Hernandez, Eunjung Yeo, Kwanghee Choi +12

The limited availability of dysarthric speech data makes cross-lingual detection an important but challenging problem. A key difficulty is that speech representations often encode…

cs.LG2024★ 4 cited

Differential privacy enables fair and accurate AI-based analysis of speech disorders while protecting patient data

Soroosh Tayebi Arasteh, Mahshad Lotfinia, Paula Andrea Perez-Toro +6

Speech pathology has impacts on communication abilities and quality of life. While deep learning-based models have shown potential in diagnosing these disorders, the use of sensiti…

cs.CL2024★ 1 cited

SNOBERT: A Benchmark for clinical notes entity linking in the SNOMED CT clinical terminology

Mikhail Kulyabin, Gleb Sokolov, Aleksandr Galaida +2

The extraction and analysis of insights from medical data, primarily stored in free-text formats by healthcare workers, presents significant challenges due to its unstructured natu…

eess.AS2024★ 18 cited

The Impact of Speech Anonymization on Pathology and Its Limits

Soroosh Tayebi Arasteh, Tomas Arias-Vergara, Paula Andrea Perez-Toro +6

Integration of speech into healthcare has intensified privacy concerns due to its potential as a non-invasive biomarker containing individual biometric information. In response, sp…

eess.AS2022

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…

eess.AS2021★ 13 cited

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…

cs.LG2020★ 42 cited

Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson's Disease from Speech in Three Different Languages

J. C. Vásquez-Correa, T. Arias-Vergara, C. D. Rios-Urrego +4

Parkinson's disease patients develop different speech impairments that affect their communication capabilities. The automatic assessment of the speech of the patients allows the de…