World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
8834
World Ranking
8291
National Ranking
3555

Overview

George Saon is affiliated with IBM in the United States. Their research is primarily situated within the field of Computer Science, with a focus on Artificial Intelligence, Signal Processing, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, and Information Systems.

Their work extensively covers various topics, including:

  • Speech Recognition and Synthesis
  • Speech and Audio Processing
  • Natural Language Processing Techniques
  • Topic Modeling
  • Music and Audio Processing
  • Speech and dialogue systems
  • Neural Networks and Applications

George Saon has contributed to multiple papers of relevance within the speech recognition and acoustic modeling communities. Some recent publications include:

  • Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies, 2020, IEEE Signal Processing Magazine
  • Integrating Text Inputs for Training and Adapting RNN Transducer ASR Models, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Effect and Analysis of Large-scale Language Model Rescoring on Competitive ASR Systems, 2022, Interspeech 2022
  • Towards Reducing the Need for Speech Training Data to Build Spoken Language Understanding Systems, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Speech Recognition Using Biologically-Inspired Neural Networks, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

They frequently collaborate with other researchers such as Brian Kingsbury, Xiaodong Cui, Samuel Thomas, Hong-Kwang Jeff Kuo, and Gakuto Kurata.

The venues where George Saon publishes most include:

  • arXiv (Cornell University)
  • Interspeech 2022
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE Signal Processing Magazine
  • IEEE Transactions on Audio Speech and Language Processing

Their contributions span areas of research that integrate deep neural network training strategies, the application of recurrent neural networks in speech recognition models, improvements in language model rescoring, and methodologies to reduce training data requirements for spoken language understanding systems.

Best Publications

  • Deep Convolutional Neural Networks for Large-scale Speech Tasks

    Tara N. Sainath;Brian Kingsbury;George Saon;Hagen Soltau

  • Speaker adaptation of neural network acoustic models using i-vectors

    George Saon;Hagen Soltau;David Nahamoo;Michael Picheny

  • Boosted MMI for model and feature-space discriminative training

    D. Povey;D. Kanevsky;B. Kingsbury;B. Ramabhadran

  • fMPE: discriminatively trained features for speech recognition

    D. Povey;B. Kingsbury;L. Mangu;G. Saon

  • English Conversational Telephone Speech Recognition by Humans and Machines

    George Saon;Gakuto Kurata;Tom Sercu;Kartik Audhkhasi

  • Maximum likelihood discriminant feature spaces

    G. Saon;M. Padmanabhan;R. Gopinath;S. Chen

  • Improvements to Deep Convolutional Neural Networks for LVCSR

    Tara N. Sainath;Brian Kingsbury;Abdel-rahman Mohamed;George E. Dahl

  • The IBM 2016 English Conversational Telephone Speech Recognition System

    George Saon;Tom Sercu;Steven J. Rennie;Hong-Kwang Jeff Kuo

  • Large-Vocabulary Continuous Speech Recognition Systems: A Look at Some Recent Advances

    G. Saon;Jen-Tzung Chien

  • The IBM Attila speech recognition toolkit

    Hagen Soltau;George Saon;Brian Kingsbury

  • Advances in speech transcription at IBM under the DARPA EARS program

    S.F. Chen;B. Kingsbury;Lidia Mangu;D. Povey

  • The IBM 2004 conversational telephony system for rich transcription

    H. Soltau;B. Kingsbury;L. Mangu;D. Povey

  • The IBM 2015 English Conversational Telephone Speech Recognition System

    George Saon;Hong-Kwang Jeff Kuo;Steven J. Rennie;Michael Picheny

  • Analyzing convolutional neural networks for speech activity detection in mismatched acoustic conditions

    Samuel Thomas;Sriram Ganapathy;George Saon;Hagen Soltau

  • Direct Acoustics-to-Word Models for English Conversational Speech Recognition

    Kartik Audhkhasi;Bhuvana Ramabhadran;George Saon;Michael Picheny

  • Building Competitive Direct Acoustics-to-Word Models for English Conversational Speech Recognition

    Kartik Audhkhasi;Brian Kingsbury;Bhuvana Ramabhadran;George Saon

  • Joint training of convolutional and non-convolutional neural networks

    Hagen Soltau;George Saon;Tara N. Sainath

  • Anatomy of an extremely fast LVCSR decoder.

    George Saon;Daniel Povey;Geoffrey Zweig

  • Feature and model space speaker adaptation with full covariance Gaussians.

    Daniel Povey;George Saon

  • Data-driven approach to designing compound words for continuous speech recognition

    G. Saon;M. Padmanabhan

Frequent Co-Authors

Brian Kingsbury
Brian Kingsbury IBM (United States)
Michael Picheny
Michael Picheny IBM (United States)
Hagen Soltau
Hagen Soltau Google (United States)
Bhuvana Ramabhadran
Bhuvana Ramabhadran Google (United States)
Daniel Povey
Daniel Povey Xiaomi (China)
Tara N. Sainath
Tara N. Sainath Google (United States)
Jen-Tzung Chien
Jen-Tzung Chien National Yang Ming Chiao Tung University
David Nahamoo
David Nahamoo Pyron Inc.
Ramesh A. Gopinath
Ramesh A. Gopinath IBM (United States)
Abdel-rahman Mohamed
Abdel-rahman Mohamed Facebook (United States)

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