4 citations · 7 across the 7 of their papers we have counts for
7 papers · 1 filter
Speech as a Biomarker for Disease Detection
Catarina Botelho, Alberto Abad, Tanja Schultz +1
Speech is a rich biomarker that encodes substantial information about the health of a speaker, and thus it has been proposed for the detection of numerous diseases, achieving promi…
Using Self-Supervised Feature Extractors with Attention for Automatic COVID-19 Detection from Speech
John Mendonça, Rubén Solera-Ureña, Alberto Abad +1
The ComParE 2021 COVID-19 Speech Sub-challenge provides a test-bed for the evaluation of automatic detectors of COVID-19 from speech. Such models can be of value by providing test…
The INESC-ID Multi-Modal System for the ADReSS 2020 Challenge
Anna Pompili, Thomas Rolland, Alberto Abad
This paper describes a multi-modal approach for the automatic detection of Alzheimer's disease proposed in the context of the INESC-ID Human Language Technology Laboratory particip…
Assessment of Parkinson's Disease Medication State through Automatic Speech Analysis
Anna Pompili, Rubén Solera-Ureña, Alberto Abad +5
Parkinson's disease (PD) is a progressive degenerative disorder of the central nervous system characterized by motor and non-motor symptoms. As the disease progresses, patients alt…
Pathological speech detection using x-vector embeddings
Catarina Botelho, Francisco Teixeira, Thomas Rolland +2
The potential of speech as a non-invasive biomarker to assess a speaker's health has been repeatedly supported by the results of multiple works, for both physical and psychological…
Cross lingual transfer learning for zero-resource domain adaptation
Alberto Abad, Peter Bell, Andrea Carmantini +1
We propose a method for zero-resource domain adaptation of DNN acoustic models, for use in low-resource situations where the only in-language training data available may be poorly…