World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
5150
World Ranking
12612
National Ranking
29

Overview

Pavel Matějka is affiliated with Brno University of Technology in the Czech Republic. Their research spans several fields, primarily focusing on psychology and engineering.

Their key areas of study include:

  • Psychology
  • Engineering

They also explore numerous specialized subfields such as:

  • Civil and Structural Engineering
  • Plant Science
  • Mechanical Engineering
  • Education
  • Applied Psychology

The main topics of Pavel Matějka's work cover a blend of engineering and psychological disciplines, including:

  • Soil Mechanics and Vehicle Dynamics
  • Smart Agriculture and AI
  • Agricultural Engineering and Mechanization
  • Education, Psychology, and Social Research
  • Digital Mental Health Interventions
  • Mental Health via Writing
  • Psychotherapy Techniques and Applications

Their recent published papers illustrate the intersection of these fields:

  • Comparison of Four RTK Receivers Operating in the Static and Dynamic Modes Using Measurement Robotic Arm, 2021, Sensors
  • Deep learning v psychoterapii: Strojová analýza nahrávek terapeutických sezení, 2021, E-psychologie
  • DeePsy: Představení online nástroje pro zpětnou vazbu v psychoterapii, 2023, Psychoterapie

Pavel Matějka has collaborated frequently with several coauthors, notably:

  • Tomáš Řiháček
  • Jan Kadeřábek
  • V. Shapoval
  • M. Kroulík
  • František Kumhála

In terms of publication venues, their work has appeared mainly in:

  • Sensors
  • E-psychologie
  • Psychoterapie

Best Publications

  • Fusion of Heterogeneous Speaker Recognition Systems in the STBU Submission for the NIST Speaker Recognition Evaluation 2006

    N. Brummer;L. Burget;J.H. Cernocky;O. Glembek

  • Language Recognition in iVectors Space

    David Martínez González;Oldrich Plchot;Lukás Burget;Ondrej Glembek

  • Bi-Modal Person Recognition on a Mobile Phone: Using Mobile Phone Data

    Christopher McCool;Sebastien Marcel;Abdenour Hadid;Matti Pietikainen

  • Hierarchical Structures of Neural Networks for Phoneme Recognition

    P. Schwarz;P. Matejka;J. Cernocky

  • Comparison of keyword spotting approaches for informal continuous speech.

    Igor Szöke;Petr Schwarz;Pavel Matejka;Lukás Burget

  • Full-covariance UBM and heavy-tailed PLDA in i-vector speaker verification

    Pavel Matejka;Ondrej Glembek;Fabio Castaldo;M.J. Alam

  • Discriminatively trained Probabilistic Linear Discriminant Analysis for speaker verification

    Lukas Burget;Oldrich Plchot;Sandro Cumani;Ondrej Glembek

  • Analysis of Feature Extraction and Channel Compensation in a GMM Speaker Recognition System

    L. Burget;P. Matejka;P. Schwarz;O. Glembek

  • Phonotactic language identification using high quality phoneme recognition.

    Pavel Matejka;Petr Schwarz;Jan Cernocký;Pavel Chytil

  • Simplification and optimization of i-vector extraction

    Ondrej Glembek;Lukas Burget;Pavel Matejka;Martin Karafiat

  • Towards Lower Error Rates in Phoneme Recognition

    Petr Schwarz;Pavel Matějka;Jan Černocký

  • Neural Network Bottleneck Features for Language Identification

    Unknown

  • Mobile Biometrics (MoBio): Joint Face and Voice Verification for a Mobile Platform

    P. Tresadern;C. McCool;N. Poh;P. Matejka

  • Brno University of Technology System for NIST 2005 Language Recognition Evaluation

    P. Matejka;L. Burget;P. Sckwarz;J. Cernocky

  • Developing a Speech Activity Detection System for the DARPA RATS Program.

    Tim Ng;Bing Zhang;Long Nguyen;Spyros Matsoukas

  • Analysis of DNN approaches to speaker identification

    Pavel Matejka;Ondrej Glembek;Ondrej Novotny;Oldrich Plchot

  • BUT System Description to VoxCeleb Speaker Recognition Challenge 2019

    Hossein Zeinali;Shuai Wang;Anna Silnova;Pavel Matejka

  • Analysis of Score Normalization in Multilingual Speaker Recognition.

    Pavel Matějka;Ondřej Novotný;Oldřich Plchot;Lukáš Burget

  • Discriminative Training Techniques for Acoustic Language Identification

    L. Burget;P. Matejka;J. Cernocky

  • iVector-based discriminative adaptation for automatic speech recognition

    Martin Karafiat;Lukas Burget;Pavel Matejka;Ondrej Glembek

  • Combination of strongly and weakly constrained recognizers for reliable detection of OOVS

    L. Burget;P. Schwarz;P. Matejka;M. Hannemann

  • Mobile Biometrics: Combined Face and Voice Verification for a Mobile Platform

    P. Tresadern;T. F. Cootes;N. Poh;P. Matejka

  • Phoneme based acoustics keyword spotting in informal continuous speech

    Igor Szöke;Petr Schwarz;Pavel Matějka;Lukáš Burget

Frequent Co-Authors

Lukas Burget
Lukas Burget Brno University of Technology
Martin Karafiat
Martin Karafiat Brno University of Technology
Hynek Hermansky
Hynek Hermansky Johns Hopkins University
Conrad Sanderson
Conrad Sanderson Commonwealth Scientific and Industrial Research Organisation
Sébastien Marcel
Sébastien Marcel Idiap Research Institute
Björn Schuller
Björn Schuller Imperial College London
Sethuraman Panchanathan
Sethuraman Panchanathan Arizona State University
Jean-François Bonastre
Jean-François Bonastre University of Avignon
Josef Kittler
Josef Kittler University of Surrey
Patrick Kenny
Patrick Kenny École de Technologie Supérieure

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA unlocks numerous career opportunities. Many students also consider adjacent STEM pathways, as these fields often overlap in skills and job prospects. Popular online degrees include mechanical engineering, physics, data science, and electrical engineering.

Affordability is a key concern. Finding a mechanical engineering degree cost that fits your budget can make a big difference when planning your education. For those interested in the theoretical side of science, there are accredited online physics degrees that provide flexibility for working professionals or remote learners.

Data science is another rapidly growing field, with more universities offering data science degrees online—often at competitive prices. Finally, students keen on technology and innovation might consider online electrical engineering courses USA to expand their expertise.

Whether you’re pursuing computer science or a related discipline, these online pathways can help you build a versatile and rewarding tech career in the USA.

Best Scientists Citing Pavel Matějka

Trending Scientists