4 citations · 7 across the 5 of their papers we have counts for
8 papers
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…
Domain Adaptation in Dialogue Systems using Transfer and Meta-Learning
Rui Ribeiro, Alberto Abad, José Lopes
Current generative-based dialogue systems are data-hungry and fail to adapt to new unseen domains when only a small amount of target data is available. Additionally, in real-world…
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances
Ali Shahin Shamsabadi, Francisco Sepúlveda Teixeira, Alberto Abad +3
Speaker identification models are vulnerable to carefully designed adversarial perturbations of their input signals that induce misclassification. In this work, we propose a white-…
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…