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Computer Science

D-Index
34
Citations
12506
World Ranking
11884
National Ranking
25

Overview

Martin Karafiat is affiliated with Brno University of Technology in the Czech Republic, focusing primarily on research in the field of Computer Science. Their work emphasizes several subfields including Signal Processing, Artificial Intelligence, and Experimental and Cognitive Psychology.

The scientist's research extensively covers topics related to Speech Recognition and Synthesis, Speech and Audio Processing, Music and Audio Processing, Phonetics and Phonology Research, and Natural Language Processing Techniques. These areas highlight a strong involvement in audio and speech-related computational technologies.

Martin Karafiat has published multiple papers in both highly accessible pre-publication repositories and peer-reviewed journals. The venues where they frequently publish include:

  • arXiv (Cornell University)
  • International Journal of Speech Technology

Representative recent publications include:

  • "Comparison of wav2vec 2.0 models on three speech processing tasks," 2024, International Journal of Speech Technology
  • "BUT Opensat 2019 Speech Recognition System," 2020, arXiv (Cornell University)
  • "BCN2BRNO: ASR System Fusion for Albayzin 2020 Speech to Text Challenge," 2021, arXiv (Cornell University)
  • "BUT CHiME-7 system description," 2023, arXiv (Cornell University)
  • "Adapting Diarization-Conditioned Whisper for End-to-End Multi-Talker Speech Recognition," 2025, arXiv (Cornell University)

The authorship record demonstrates collaboration with a number of frequent co-authors, including Karel Veselý, Jaň Černocký, Igor Szöke, Martin Kocour, and Marie Kunešová. These partnerships reflect ongoing cooperative efforts in speech technology and related fields.

Best Publications

  • Recurrent neural network based language model

    Tomas Mikolov;Martin Karafiát;Lukás Burget;Jan Cernocký

  • Probabilistic and Bottle-Neck Features for LVCSR of Meetings

    F. Grezl;M. Karafiat;S. Kontar;J. Cernocky

  • The subspace Gaussian mixture model-A structured model for speech recognition

    Daniel Povey;Lukáš Burget;Mohit Agarwal;Pinar Akyazi

  • 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

  • Recurrent Neural Network based Language Modeling in Meeting Recognition

    Stefan Kombrink;Tomas Mikolov;Martin Karafiát;Lukás Burget

  • Comparison of keyword spotting approaches for informal continuous speech.

    Igor Szöke;Petr Schwarz;Pavel Matejka;Lukás Burget

  • The language-independent bottleneck features

    Karel Vesely;Martin Karafiat;Frantisek Grezl;Milos Janda

  • Subspace Gaussian Mixture Models for speech recognition

    Daniel Povey;Lukas Burget;Mohit Agarwal;Pinar Akyazi

  • Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models

    Lukas Burget;Petr Schwarz;Mohit Agarwal;Pinar Akyazi

  • Generating exact lattices in the WFST framework

    Daniel Povey;Mirko Hannemann;Gilles Boulianne;Lukas Burget

  • Simplification and optimization of i-vector extraction

    Ondrej Glembek;Lukas Burget;Pavel Matejka;Martin Karafiat

  • The AMI System for the Transcription of Speech in Meetings

    T. Hain;V. Wan;L. Burget;M. Karafiat

  • Transcribing Meetings With the AMIDA Systems

    T. Hain;L. Burget;J. Dines;P. N. Garner

  • Multilingual Sequence-to-Sequence Speech Recognition: Architecture, Transfer Learning, and Language Modeling

    Jaejin Cho;Murali Karthick Baskar;Ruizhi Li;Matthew Wiesner

  • Convolutive Bottleneck Network features for LVCSR

    Karel Vesely;Martin Karafiat;Frantisek Grezl

  • Adaptation of multilingual stacked bottle-neck neural network structure for new language

    Frantisek Grezl;Martin Karafiat;Karel Vesely

  • Score normalization and system combination for improved keyword spotting

    Damianos Karakos;Richard Schwartz;Stavros Tsakalidis;Le Zhang

  • Investigation into bottle-neck features for meeting speech recognition.

    Frantisek Grézl;Martin Karafiát;Lukás Burget

  • iVector-based discriminative adaptation for automatic speech recognition

    Martin Karafiat;Lukas Burget;Pavel Matejka;Ondrej Glembek

  • The AMI meeting transcription system: progress and performance

    Thomas Hain;Lukas Burget;John Dines;Giulia Garau

  • The development of the AMI system for the transcription of speech in meetings

    Thomas Hain;Lukas Burget;John Dines;Iain McCowan

Frequent Co-Authors

Lukas Burget
Lukas Burget Brno University of Technology
Jan Cernocky
Jan Cernocky Brno University of Technology
Thomas Hain
Thomas Hain University of Sheffield
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Daniel Povey
Daniel Povey Xiaomi (China)
Richard Rose
Richard Rose Google (United States)
Steve Renals
Steve Renals University of Edinburgh
Tomas Mikolov
Tomas Mikolov Czech Technical University in Prague
Pavel Matějka
Pavel Matějka Brno University of Technology
Iain A. McCowan
Iain A. McCowan Queensland University of Technology

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