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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
114
Citations
63174
World Ranking
191
National Ranking
11

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award
  • 2011 - IEEE Fellow For contributions to statistical language modeling, statistical machine translation, and large vocabulary speech recognition

Overview

Hermann Ney is affiliated with RWTH Aachen University in Germany and has made significant contributions in the field of computer science, particularly focusing on artificial intelligence and signal processing. Their research encompasses a wide range of specialized topics including speech recognition and synthesis, natural language processing techniques, and topic modeling.

Their work covers domains such as speech and audio processing, music and audio processing, speech and dialogue systems, and multimodal machine learning applications. This diverse set of research interests is reflected in numerous publications, primarily appearing in venues like arXiv (Cornell University) and ICASSP 2022, the IEEE International Conference on Acoustics, Speech and Signal Processing.

Some recent notable papers by Hermann Ney include:

  • Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented Dialog, 2021, arXiv (Cornell University)
  • Conformer-Based Hybrid ASR System For Switchboard Dataset, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Why does CTC result in peaky behavior?, 2021, arXiv (Cornell University)
  • On Language Model Integration for RNN Transducer Based Speech Recognition, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change, 2024, arXiv (Cornell University)

Hermann Ney has collaborated frequently with several researchers, highlighting teamwork and interdisciplinary research. Frequent co-authors include:

  • Ralf Schlüter (55 joint publications)
  • Wei Zhou (20 joint publications)
  • Mohammad Zeineldeen (17 joint publications)
  • Wilfried Michel (13 joint publications)
  • Christoph Lüscher (11 joint publications)

Their works have been published extensively in venues such as:

  • arXiv (Cornell University) with 64 publications
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) with 4 publications
  • Interspeech 2022 with 4 publications
  • RWTH Publications (RWTH Aachen) with 3 publications
  • 2022 IEEE Spoken Language Technology Workshop (SLT) with 2 publications

In 2011, Hermann Ney was named an IEEE Fellow for contributions to statistical language modeling, statistical machine translation, and large vocabulary speech recognition, indicating recognition by peers in the field.

Best Publications

  • A systematic comparison of various statistical alignment models

    Franz Josef Och;Hermann Ney

  • LSTM Neural Networks for Language Modeling.

    Martin Sundermeyer;Ralf Schlüter;Hermann Ney

  • Improved backing-off for M-gram language modeling

    R. Kneser;H. Ney

  • Discriminative Training and Maximum Entropy Models for Statistical Machine Translation

    Franz Josef Och;Hermann Ney

  • Improved statistical alignment models

    Franz Josef Och;Hermann Ney

  • The Alignment Template Approach to Statistical Machine Translation

    Franz Josef Och;Hermann Ney

  • HMM-based word alignment in statistical translation

    Stephan Vogel;Hermann Ney;Christoph Tillmann

  • On structuring probabilistic dependences in stochastic language modelling

    Hermann Ney;Ute Essen;Reinhard Kneser

  • Improved Alignment Models for Statistical Machine Translation

    Franz Josef Och;Christoph Tillmann;Hermann Ney

  • Joint-sequence models for grapheme-to-phoneme conversion

    Maximilian Bisani;Hermann Ney

  • Features for image retrieval: an experimental comparison

    Thomas Deselaers;Daniel Keysers;Hermann Ney

  • Confidence measures for large vocabulary continuous speech recognition

    F. Wessel;R. Schluter;K. Macherey;H. Ney

  • Neural Sign Language Translation

    Necati Cihan Camgoz;Simon Hadfield;Oscar Koller;Hermann Ney

  • A word graph algorithm for large vocabulary continuous speech recognition

    Stefan Ortmanns;Hermann Ney;Xavier L. Aubert

  • From feedforward to recurrent LSTM neural networks for language modeling

    Martin Sundermeyer;Hermann Ney;Ralf Schlüter

  • The use of a one-stage dynamic programming algorithm for connected word recognition

    H. Ney

  • Linear discriminant analysis for improved large vocabulary continuous speech recognition

    R. Haeb-Umbach;H. Ney

  • The 2005 PASCAL visual object classes challenge

    Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

  • Continuous Sign Language Recognition: Towards Large Vocabulary Statistical Recognition Systems Handling Multiple Signers

    Oscar Koller;Jens Forster;Hermann Ney

  • Phrase-Based Statistical Machine Translation

    Richard Zens;Franz Josef Och;Hermann Ney

  • A word graph algorithm for large vocabulary, continuous speech recognition.

    Hermann Ney;Xavier L. Aubert

Frequent Co-Authors

Ralf Schlüter
Ralf Schlüter RWTH Aachen University
Daniel Keysers
Daniel Keysers Google (United States)
Thomas Deselaers
Thomas Deselaers Apple (United States)
Georg Heigold
Georg Heigold German Research Centre for Artificial Intelligence
Franz Josef Och
Franz Josef Och Google (United States)
Reinhold Haeb-Umbach
Reinhold Haeb-Umbach University of Paderborn
Enrique Vidal
Enrique Vidal Universitat Politècnica de València
Stephan Vogel
Stephan Vogel University of Graz
Alex Waibel
Alex Waibel Carnegie Mellon University
Francisco Casacuberta
Francisco Casacuberta Universitat Politècnica de València

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