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 47 Citations 8,096 249 World Ranking 3252 National Ranking 201

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Speech recognition
  • Statistics

His primary scientific interests are in Speech recognition, Speech synthesis, Artificial intelligence, Natural language processing and Hidden Markov model. His Speech recognition research incorporates themes from Artificial neural network and Context. The Speech synthesis study which covers Speaker recognition that intersects with Spoofing attack.

The various areas that he examines in his Artificial intelligence study include Perception, Simulation, Phone, Machine learning and Pattern recognition. Simon King combines subjects such as Pronunciation, Database, Range, Speech corpus and Text to speech synthesis with his study of Natural language processing. His Hidden Markov model research includes elements of Sound quality, Feature extraction, Robustness and Decision tree.

His most cited work include:

  • Deep neural networks employing Multi-Task Learning and stacked bottleneck features for speech synthesis (193 citations)
  • Merlin: An Open Source Neural Network Speech Synthesis System (192 citations)
  • Objective Distance Measures for Spectral Discontinuities in Concatenative Speech Synthesis (187 citations)

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

Simon King mainly investigates Speech recognition, Speech synthesis, Artificial intelligence, Natural language processing and Hidden Markov model. His studies link Artificial neural network with Speech recognition. His studies deal with areas such as Intelligibility, Parametric statistics, Perception and Voice activity detection as well as Speech synthesis.

The concepts of his Artificial intelligence study are interwoven with issues in Context and Pattern recognition. His research in Natural language processing intersects with topics in Pronunciation and Word. His Hidden Markov model research is multidisciplinary, relying on both Feature extraction and Adaptation.

He most often published in these fields:

  • Speech recognition (75.29%)
  • Speech synthesis (52.94%)
  • Artificial intelligence (43.82%)

What were the highlights of his more recent work (between 2015-2021)?

  • Speech recognition (75.29%)
  • Speech synthesis (52.94%)
  • Artificial intelligence (43.82%)

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

Simon King mostly deals with Speech recognition, Speech synthesis, Artificial intelligence, Artificial neural network and Parametric statistics. His Speech recognition research integrates issues from Variation and Waveform. His work carried out in the field of Speech synthesis brings together such families of science as Statistical model and Hidden Markov model.

His Hidden Markov model research includes themes of Decision tree, Feature extraction, Speaker recognition and Parametric model. His Artificial intelligence research incorporates elements of Machine learning, Pattern recognition, State and Natural language processing. In the field of Artificial neural network, his study on Recurrent neural network overlaps with subjects such as Merlin, Open source, Noise and Mean opinion score.

Between 2015 and 2021, his most popular works were:

  • Merlin: An Open Source Neural Network Speech Synthesis System (192 citations)
  • Investigating gated recurrent networks for speech synthesis (95 citations)
  • From HMMS to DNNS: Where do the improvements come from? (53 citations)

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

  • Artificial intelligence
  • Speech recognition
  • Statistics

His main research concerns Speech recognition, Speech synthesis, Artificial intelligence, Artificial neural network and Parametric statistics. His Speech recognition study combines topics from a wide range of disciplines, such as Control and Spoofing attack. His studies in Speech synthesis integrate themes in fields like Intonation, Prosody, Statistical model and Hidden Markov model.

His study looks at the intersection of Hidden Markov model and topics like Feature extraction with Representation, Speaker recognition and Computer security. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Markov model. His research investigates the connection between Artificial neural network and topics such as Pattern recognition that intersect with issues in Parametric model and Hybrid system.

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

Merlin: An Open Source Neural Network Speech Synthesis System

Zhizheng Wu;Oliver Watts;Simon King.
9th ISCA Speech Synthesis Workshop (2016)

313 Citations

The Blizzard Challenge 2008

Simon King;Robert A J Clark;Catherine Mayo;Vasilis Karaiskos.
(2008)

296 Citations

Objective Distance Measures for Spectral Discontinuities in Concatenative Speech Synthesis

Jithendra Vepa;Simon King;Paul Taylor.
conference of the international speech communication association (2002)

285 Citations

Deep neural networks employing Multi-Task Learning and stacked bottleneck features for speech synthesis

Zhizheng Wu;Cassia Valentini-Botinhao;Oliver Watts;Simon King.
international conference on acoustics, speech, and signal processing (2015)

279 Citations

Detection of phonological features in continuous speech using neural networks

Simon King;Paul Taylor.
Computer Speech & Language (2000)

250 Citations

Speech production knowledge in automatic speech recognition.

Simon King;Joe Frankel;Karen Livescu;Erik McDermott.
Journal of the Acoustical Society of America (2007)

233 Citations

Robust Speaker-Adaptive HMM-Based Text-to-Speech Synthesis

J. Yamagishi;T. Nose;H. Zen;Zhen-Hua Ling.
IEEE Transactions on Audio, Speech, and Language Processing (2009)

232 Citations

Multisyn: Open-domain unit selection for the Festival speech synthesis system

Robert A. J. Clark;Korin Richmond;Simon King.
Speech Communication (2007)

188 Citations

A study of speaker adaptation for DNN-based speech synthesis

Zhizheng Wu;Pawel Swietojanski;Christophe Veaux;Stephen Renals.
conference of the international speech communication association (2015)

139 Citations

Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 JHU Summer workshop

K. Livescu;O. Cetin;M. Hasegawa-Johnson;S. King.
international conference on acoustics, speech, and signal processing (2007)

135 Citations

Best Scientists Citing Simon King

Junichi Yamagishi

Junichi Yamagishi

National Institute of Informatics

Publications: 140

Haizhou Li

Haizhou Li

Chinese University of Hong Kong, Shenzhen

Publications: 62

Tomoki Toda

Tomoki Toda

Nagoya University

Publications: 48

Zhen-Hua Ling

Zhen-Hua Ling

University of Science and Technology of China

Publications: 41

Keiichi Tokuda

Keiichi Tokuda

Nagoya Institute of Technology

Publications: 41

Paavo Alku

Paavo Alku

Aalto University

Publications: 39

Thomas R. Gruber

Thomas R. Gruber

Apple (United States)

Publications: 33

Shrikanth S. Narayanan

Shrikanth S. Narayanan

University of Southern California

Publications: 29

Steve Renals

Steve Renals

University of Edinburgh

Publications: 29

Satoshi Nakamura

Satoshi Nakamura

Nara Institute of Science and Technology

Publications: 29

Hervé Bourlard

Hervé Bourlard

Idiap Research Institute

Publications: 28

Helen Meng

Helen Meng

Chinese University of Hong Kong

Publications: 26

Li Deng

Li Deng

Citadel

Publications: 25

Karen Livescu

Karen Livescu

Toyota Technological Institute at Chicago

Publications: 24

Tomi Kinnunen

Tomi Kinnunen

University of Eastern Finland

Publications: 24

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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