Bálint Gyires-Tóth is a senior lecturer at BME. He conducts research on fundamental and applied machine learning since 2007. With his leadership, the first Hungarian hidden Markov-model based Text-To-Speech (TTS) system was introduced in 2008. He obtained his PhD degree with summa cum laude in January 2014. Since then, his primary research field is deep learning. His main research interests are sequential data modeling with deep learning, self-supervised learning and deep reinforcement learning. He also participates in applied deep learning projects, like time series classification and forecast, anomaly detection, image and audio classification and natural language processing. He was involved in various successful research and commercial projects. In 2017 he was certified as NVidia Deep Learning Institute (DLI) Instructor and University Ambassador.
2005-2007 BESZTEL project: Introducing speech synthesis in mobile phones for vision-impaired users (GVOP-3.1.1.-2004-05-0485/3.0), NKFIH
2009-2011 ETOCOM (TÁMOP-4.2.2/08/1/KMR-2008-0007): Synthetic speech enhancement in infocommunication systems
2011-2013 CESAR (CEntral and South EuropeAn Resources, CIP ICT-PSP-2010-4 no. 271022), speech and language resource standardization and enhancement, EU
2012-2014 Personal Assistant to Enhance the Social Life of the Seniors (PAELIFE), Research on speech synthesizers for elderly people (B-AAL-08-1-2011-0063870), AAL EU
VUK (AAL-2014-1-183): The goal of the Visionless sUpporting frameworK (VUK) is to ease daily life for blind and visually impaired people in challenging tasks like participating in urban mobility, providing a simple, effective and affordable door to door navigation and mobility assistance solution, AAL EU
2016-2019 EUREKA / DANSPLAT: A platform for the applications of speech technologies on smartphones for the languages of the Danube region
EFOP-3.6.2-16-2017-00013: Modeling weakly coherent multi-dimensional time series with deep learning, subproject leader, NKFIH
Felsőoktatási Intézményi Kiválósági Program (FIKP): Adaptive systems and intelligent interactions, subproject leader, NKFIH
János Bolyai Research Fellowship, 2019-2021, Modeling multiscale sequential data with deep learning, Hungarian Academy of Sciences
New National Excellence Program, Bolyai+ Young Higher Education Teachers and Researchers Fellowship, 2019-2021, NKFIH
"Professional Intelligence for Automotive" (PIA), Continental Deep Machine Learning Competence Center
The European Sector Skills Alliances, 2020-2023, EU
