D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 85 Citations 91,366 284 World Ranking 323 National Ranking 204

Research.com Recognitions

Awards & Achievements

1999 - Jack S. Kilby Signal Processing Medal For far-reaching impact on the fields of digital signal processing and automatic speech recognition

1990 - Member of the National Academy of Sciences

1983 - Member of the National Academy of Engineering Contributions to digital signal processing and speech communications research.

1976 - IEEE Fellow For contributions to digital signal processing and speech communication research.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Speech recognition

Lawrence R. Rabiner spends much of his time researching Speech recognition, Artificial intelligence, Algorithm, Pattern recognition and Speech processing. As part of one scientific family, Lawrence R. Rabiner deals mainly with the area of Speech recognition, narrowing it down to issues related to the Signal, and often Digital signal processing. His studies in Artificial intelligence integrate themes in fields like Markov process, Markov chain and Natural language processing.

The Algorithm study combines topics in areas such as Pitch detection algorithm, Convolution, Overlap–add method and Bluestein's FFT algorithm. When carried out as part of a general Speech processing research project, his work on Voice activity detection and Speech analytics is frequently linked to work in Simple, therefore connecting diverse disciplines of study. His Hidden Markov model study frequently involves adjacent topics like Markov model.

His most cited work include:

  • A tutorial on hidden Markov models and selected applications in speech recognition (20443 citations)
  • Fundamentals of speech recognition (6607 citations)
  • An introduction to hidden Markov models (3817 citations)

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

Lawrence R. Rabiner mainly focuses on Speech recognition, Artificial intelligence, Word, Pattern recognition and Vocabulary. His research on Speech recognition frequently links to adjacent areas such as Set. The concepts of his Artificial intelligence study are interwoven with issues in Signal and Natural language processing.

Lawrence R. Rabiner has researched Word in several fields, including Dynamic time warping, Cluster analysis, Algorithm, String and Pattern recognition. Lawrence R. Rabiner has included themes like Markov process, Markov chain and Markov model in his Hidden Markov model study. His work carried out in the field of Speech processing brings together such families of science as Digital signal processing and Speech synthesis.

He most often published in these fields:

  • Speech recognition (55.81%)
  • Artificial intelligence (30.00%)
  • Word (21.63%)

What were the highlights of his more recent work (between 1993-2017)?

  • Speech recognition (55.81%)
  • Artificial intelligence (30.00%)
  • Multimedia (3.49%)

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

Lawrence R. Rabiner mainly investigates Speech recognition, Artificial intelligence, Multimedia, Speech processing and Speech technology. His work in Speech analytics, Acoustic model, Dictation, Speaker recognition and Transcription are all subfields of Speech recognition research. His work deals with themes such as Natural language processing and Pattern recognition, which intersect with Artificial intelligence.

His Speech processing study combines topics from a wide range of disciplines, such as Telecommunications network and Speech synthesis. Lawrence R. Rabiner focuses mostly in the field of Speech technology, narrowing it down to topics relating to Digital signal processing and, in certain cases, Multidimensional signal processing, Speech enhancement and Acoustics. His research in Hidden Markov model tackles topics such as Sigmoid function which are related to areas like Outlier and Covariance.

Between 1993 and 2017, his most popular works were:

  • Multirate Digital Signal Processing (601 citations)
  • Active user registry (255 citations)
  • Pots/packet bridge (254 citations)

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

  • Artificial intelligence
  • Statistics
  • Algorithm

The scientist’s investigation covers issues in Speech recognition, Multimedia, Speech technology, Speech processing and Artificial intelligence. His Speech recognition study integrates concerns from other disciplines, such as Matching and Natural language. Lawrence R. Rabiner interconnects IP Multimedia Subsystem, User interface, Digital signal processing, Telecommunications and Key in the investigation of issues within Multimedia.

His Digital signal processing research includes elements of Voice activity detection and Signal processing. His work is dedicated to discovering how Speech processing, Speech synthesis are connected with Wireless network, Information access, Voice command device, Computer telephony integration and Speech coding and other disciplines. His Artificial intelligence research focuses on subjects like Natural language processing, which are linked to Speech corpus, Utterance, Transcription and TRACE.

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.

Best Publications

A tutorial on hidden Markov models and selected applications in speech recognition

L.R. Rabiner.
Proceedings of the IEEE (1989)

37974 Citations

Fundamentals of speech recognition

Lawrence Rabiner;Biing-Hwang Juang.
(1993)

13487 Citations

An introduction to hidden Markov models

L. Rabiner;B. Juang.
IEEE Assp Magazine (1986)

5940 Citations

Theory and application of digital signal processing

L. R. Rabiner;B. Gold;C. K. Yuen.
(1975)

5635 Citations

Digital Processing of Speech Signals

Lawrence R. Rabiner;Ronald W. Schafer.
(1978)

4950 Citations

Multirate Digital Signal Processing

Lawrence R. Rabiner.
(2019)

2645 Citations

Hidden Markov Models for Speech Recognition

B. H. Juang;L. R. Rabiner.
(1991)

2033 Citations

A computer program for designing optimum FIR linear phase digital filters

J. McClellan;T. Parks;L. Rabiner.
IEEE Transactions on Audio and Electroacoustics (1973)

1628 Citations

An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition

S. E. Levinson;L. R. Rabiner;M. M. Sondhi.
Bell System Technical Journal (1983)

1432 Citations

A unified approach to short-time Fourier analysis and synthesis

J.B. Allen;L.R. Rabiner.
Proceedings of the IEEE (1977)

1104 Citations

Best Scientists Citing Lawrence R. Rabiner

Chin-Hui Lee

Chin-Hui Lee

Georgia Institute of Technology

Publications: 150

Thomas S. Huang

Thomas S. Huang

University of Illinois at Urbana-Champaign

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Vikram Krishnamurthy

Vikram Krishnamurthy

Cornell University

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Horst Bunke

Horst Bunke

University of Bern

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Li Deng

Li Deng

Citadel

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Gerhard Rigoll

Gerhard Rigoll

Technical University of Munich

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Kuldip K. Paliwal

Kuldip K. Paliwal

Griffith University

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Hervé Bourlard

Hervé Bourlard

Idiap Research Institute

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Hermann Ney

Hermann Ney

RWTH Aachen University

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Samy Bengio

Samy Bengio

Google (United States)

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Yoshihiko Nakamura

Yoshihiko Nakamura

University of Tokyo

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B. Yegnanarayana

B. Yegnanarayana

International Institute of Information Technology, Hyderabad

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Lawrence Carin

Lawrence Carin

King Abdullah University of Science and Technology

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Tapio Saramaki

Tapio Saramaki

Tampere University

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Shrikanth S. Narayanan

Shrikanth S. Narayanan

University of Southern California

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P.P. Vaidyanathan

P.P. Vaidyanathan

California Institute of Technology

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

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