H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 60 Citations 12,584 128 World Ranking 1562 National Ranking 872

Research.com Recognitions

Awards & Achievements

2004 - IEEE Fellow For contributions to statistical methods for human language processing.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Speech recognition

His primary scientific interests are in Artificial intelligence, Speech recognition, Natural language processing, Language model and Pattern recognition. The Word research Jerome R. Bellegarda does as part of his general Artificial intelligence study is frequently linked to other disciplines of science, such as Set and Key, therefore creating a link between diverse domains of science. In the field of Speech recognition, his study on Speech processing and Speech synthesis overlaps with subjects such as Front and back ends and Sequence.

He regularly ties together related areas like Machine learning in his Natural language processing studies. His research in Language model intersects with topics in Latent semantic analysis, Context, Representation and Vocabulary. His Pattern recognition study combines topics from a wide range of disciplines, such as Vector space and Probabilistic latent semantic analysis.

His most cited work include:

  • Method, device, and graphical user interface providing word recommendations for text input (290 citations)
  • Statistical language model adaptation: review and perspectives (274 citations)
  • Large-vocabulary speech recognition using an integrated syntactic and semantic statistical language model (258 citations)

What are the main themes of his work throughout his whole career to date?

Jerome R. Bellegarda mostly deals with Artificial intelligence, Natural language processing, Speech recognition, Word and Latent semantic analysis. His Artificial intelligence research integrates issues from Context and Pattern recognition. His work in the fields of Natural language processing, such as Natural language, Language identification and Latent semantic mapping, intersects with other areas such as Sequence.

His work investigates the relationship between Speech recognition and topics such as Pronunciation that intersect with problems in Orthographic projection, Transcription, Proper noun and Space. The various areas that Jerome R. Bellegarda examines in his Word study include Acoustic model, Representation and Inference. His Latent semantic analysis research focuses on Probabilistic latent semantic analysis and how it connects with Document-term matrix.

He most often published in these fields:

  • Artificial intelligence (66.67%)
  • Natural language processing (49.59%)
  • Speech recognition (43.90%)

What were the highlights of his more recent work (between 2017-2020)?

  • Artificial intelligence (66.67%)
  • Natural language processing (49.59%)
  • Real-time computing (1.63%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Natural language processing, Real-time computing, Handwriting recognition and Generative grammar. His Artificial intelligence research focuses on Handwriting and Deep learning. Jerome R. Bellegarda interconnects Transcription, Cursive and Rendering in the investigation of issues within Handwriting.

As part of one scientific family, Jerome R. Bellegarda deals mainly with the area of Natural language processing, narrowing it down to issues related to the Training set, and often Word. His Handwriting recognition study combines topics in areas such as Machine learning, Speech recognition and Chinese characters. His Generative grammar research is multidisciplinary, relying on both Adversarial system, Theoretical computer science and Data set.

Between 2017 and 2020, his most popular works were:

  • The “ScribbleLens” Dutch Historical Handwriting Corpus (3 citations)
  • Systems and methods for proactively identifying and surfacing relevant content on an electronic device with a touch-sensitive display (3 citations)
  • Embedded Large–Scale Handwritten Chinese Character Recognition (1 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Speech recognition

His primary areas of investigation include Artificial intelligence, Deep learning, Handwriting, Gesture and Human–computer interaction. His research on Artificial intelligence frequently connects to adjacent areas such as Machine learning. Jerome R. Bellegarda combines subjects such as Transcription, Rendering and Natural language processing with his study of Deep learning.

Jerome R. Bellegarda performs multidisciplinary study on Handwriting and Guard in his works. His Gesture study overlaps with User interface and Content.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Statistical language model adaptation: review and perspectives

Jerome R Bellegarda.
Speech Communication (2004)

411 Citations

Method, Device, and Graphical User Interface Providing Word Recommendations for Text Input

Kenneth Kocienda;Greg Christie;Bas Ording;Scott Forstall.
(2008)

404 Citations

Large-vocabulary speech recognition using an integrated syntactic and semantic statistical language model

Jerome R. Bellegarda.
(1996)

398 Citations

Method and system for providing word recommendations for text input

Greg Christie;Bas Ording;Scott Forstall;Kenneth Kocienda.
(2007)

342 Citations

Method and system for deriving a large-span semantic language model for large-vocabulary recognition systems

Jerome R. Bellegarda;Yen-Lu Chow.
(1996)

323 Citations

Fast, language-independent method for user authentication by voice

Jerome R. Bellegarda;Kim E. A. Silverman.
(2007)

312 Citations

Method and apparatus for command recognition using data-driven semantic inference

Jerome R. Bellegarda;Kim E. A. Silverman.
(1998)

307 Citations

Multi-command single utterance input method

Sabatelli Alessandro;Gruber Thomas R;Saddler Harry J;Bellegarda Jerome Rene.
(2015)

306 Citations

Method and apparatus for improved duration modeling of phonemes

Jerome R. Bellegarda;Kim Silverman.
Journal of the Acoustical Society of America (2002)

299 Citations

Exploiting both local and global constraints for multi-span statistical language modeling

J.R. Bellegarda.
international conference on acoustics speech and signal processing (1998)

287 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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