2026 Brian Kingsbury: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	58	3522	3423	1695	1635	188	31666

Research.com Recognitions

2018 - IEEE Fellow For contributions to acoustic models for automatic speech recognition

Overview

Brian Kingsbury is affiliated with IBM in the United States. Their research spans the field of computer science, with a significant focus on artificial intelligence, signal processing, and computer vision and pattern recognition. Their work is positioned mainly within the subfields of artificial intelligence and signal processing, intersecting areas such as speech recognition and synthesis, natural language processing techniques, and multimodal machine learning applications.

The scientist's recent publications include contributions to conferences and journals with a focus on speech systems and machine learning. Notable papers include:

Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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)
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)
Towards End-to-End Integration of Dialog History for Improved Spoken Language Understanding, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Improving Generalization of Deep Neural Network Acoustic Models with Length Perturbation and N-best Based Label Smoothing, 2022, Interspeech 2022

Brian Kingsbury frequently collaborates with a group of co-authors who have contributed to multiple papers together. These include Samuel Thomas, George Saon, Xiaodong Cui, Hong-Kwang Jeff Kuo, and Andrew Rouditchenko.

Their work has been published predominantly in venues such as:

arXiv (Cornell University)
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Interspeech 2022
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Main topics covered through their research output are:

Speech Recognition and Synthesis
Speech and Audio Processing
Natural Language Processing Techniques
Speech and dialogue systems
Topic Modeling
Music and Audio Processing
Multimodal Machine Learning Applications

In 2018, Brian Kingsbury was recognized as an IEEE Fellow for their contributions to acoustic models for automatic speech recognition.

Best Publications

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

G. Hinton;Li Deng;Dong Yu;G. E. Dahl

13421
Citations
Deep Neural Networks for Acoustic Modeling in Speech Recognition

Geoffrey Hinton;Li Deng;Dong Yu;George Dahl

3219
Citations
Deep Convolutional Neural Networks for Large-scale Speech Tasks

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

1749
Citations
New types of deep neural network learning for speech recognition and related applications: an overview

Li Deng;Geoffrey Hinton;Brian Kingsbury

1456
Citations
Deep convolutional neural networks for LVCSR

Tara N. Sainath;Abdel-rahman Mohamed;Brian Kingsbury;Bhuvana Ramabhadran

1304
Citations
Low-rank matrix factorization for Deep Neural Network training with high-dimensional output targets

Tara N. Sainath;Brian Kingsbury;Vikas Sindhwani;Ebru Arisoy

727
Citations
Data augmentation for deep neural network acoustic modeling

Xiaodong Cui;Vaibhava Goel;Brian Kingsbury

488
Citations
Boosted MMI for model and feature-space discriminative training

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

478
Citations
fMPE: discriminatively trained features for speech recognition

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

375
Citations
Robust speech recognition using the modulation spectrogram

Brian E. D. Kingsbury;Brian E. D. Kingsbury;Nelson Morgan;Nelson Morgan;Steven Greenberg;Steven Greenberg

365
Citations
Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling

Brian Kingsbury

345
Citations
The modulation spectrogram: in pursuit of an invariant representation of speech

S. Greenberg;B.E.D. Kingsbury

294
Citations
Improvements to Deep Convolutional Neural Networks for LVCSR

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

273
Citations
Scalable Minimum Bayes Risk Training of Deep Neural Network Acoustic Models Using Distributed Hessian-free Optimization.

Brian Kingsbury;Tara N. Sainath;Hagen Soltau

272
Citations
Deep Neural Network Language Models

Ebru Arisoy;Tara N. Sainath;Brian Kingsbury;Bhuvana Ramabhadran

268
Citations
Very deep multilingual convolutional neural networks for LVCSR

Tom Sercu;Christian Puhrsch;Brian Kingsbury;Yann LeCun

265
Citations
Making Deep Belief Networks effective for large vocabulary continuous speech recognition

Tara N. Sainath;Brian Kingsbury;Bhuvana Ramabhadran;Petr Fousek

236
Citations
Auto-encoder bottleneck features using deep belief networks

Tara N. Sainath;Brian Kingsbury;Bhuvana Ramabhadran

233
Citations
Audio-visual deep learning for noise robust speech recognition

Jing Huang;Brian Kingsbury

213
Citations
Learning filter banks within a deep neural network framework

Tara N. Sainath;Brian Kingsbury;Abdel-rahman Mohamed;Bhuvana Ramabhadran

189
Citations
The shared views of four research groups )

Geoffrey Hinton;Li Deng;Dong Yu;George E. Dahl

8
Citations

Frequent Co-Authors

George Saon IBM (United States)

Bhuvana Ramabhadran Google (United States)

Tara N. Sainath Google (United States)

Michael Picheny IBM (United States)

Nelson Morgan International Computer Science Institute

Hagen Soltau Google (United States)

Abdel-rahman Mohamed Facebook (United States)

Daniel Povey Xiaomi (China)

Krste Asanovic University of California, Berkeley

John Wawrzynek University of California, Berkeley

External Links

Personal website of Brian Kingsbury Google Scholar page

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