Dr.-Ing. Tomás Arias Vergara

Dr.-Ing. Tomás Arias Vergara, M. Sc.

Lehrstuhl für Informatik 5 (Mustererkennung)
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 10.134
Martensstr. 3
91058 Erlangen

I received a B.S. in Electronics Engineering from the University of Antioquia (UdeA, Colombia) in 2014, a Master of Science degree at the same institution in 2017, and a Ph.D. in a joint program between the UdeA and the FAU in 2022. Since 2015, my research has focused on speech processing and machine learning methods for the analysis of pathological speech signals resulting from neurological (e.g., Parkinson’s disease), structural (e.g., children with cleft lip and palate), and perceptual (e.g., hearing loss) disorders. I have also investigated the effect of the natural aging process on speech, participated in developing Android-based applications for collecting and analyzing data from Parkinson’s disease patients and adults/children with hearing loss, and performed research on automatic methods for the analysis of high-speed videoendoscopy data of people with voice disorders.

Projects

2017

  • Training Network on Automatic Processing of PAthological Speech

    (Third Party Funds Group – Overall project)

    Term: November 1, 2017 - October 31, 2021
    Funding source: Innovative Training Networks (ITN)
    URL: https://www.tapas-etn-eu.org/

    There are an increasing number of people across Europe with debilitating speech pathologies (e.g., due to stroke, Parkinson's, etc). These groups face communication problems that can lead to social exclusion. They are now being further marginalised by a new wave of speech technology that is increasingly woven into everyday life but which is not robust to atypical speech. TAPAS is a Horizon 2020 Marie Skłodowska-Curie Actions Innovative Training Network European Training Network (MSCA-ITN-ETN) project that aims to transform the well being of these people.
    The TAPAS work programme targets three key research problems:
    (a) Detection: We will develop speech processing techniques for early detection of conditions that impact on speech production. The outcomes will be cheap and non-invasive diagnostic tools that provide early warning of the onset of progressive conditions such as Alzheimer's and Parkinson's.
    (b) Therapy: We will use newly-emerging speech processing techniques to produce automated speech therapy tools. These tools will make therapy more accessible and more individually targeted. Better therapy can increase the chances of recovering intelligible speech after traumatic events such a stroke or oral surgery.
    (c) Assisted Living: We will re-design current speech technology so that it works well for people with speech impairments and also helps in making informed clinical choices. People with speech impairments often have other co-occurring conditions making them reliant on carers. Speech-driven tools for assisted-living are a way to allow such people to live more independently.
    TAPAS adopts an inter-disciplinary and multi-sectorial approach. The consortium includes clinical practitioners, academic researchers and industrial partners, with expertise spanning speech engineering, linguistics and clinical science. All members have expertise in some element of pathological speech. This rich network will train a new generation of 15 researchers, equipping them with the skills and resources necessary for lasting success.

Publications

2024

Journal Articles

2023

Authored Books

Journal Articles

Conference Contributions

2022

Authored Books

Journal Articles

Conference Contributions

2021

Journal Articles

Conference Contributions

2020

Journal Articles

Conference Contributions

2019

Book Contributions

Conference Contributions

2018

Journal Articles

Conference Contributions

2017

Authored Books

Conference Contributions

2016

Conference Contributions