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 30 Citations 4,765 186 World Ranking 8758 National Ranking 809

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Jun Du mostly deals with Speech recognition, Artificial intelligence, Artificial neural network, Speech enhancement and Pattern recognition. The concepts of his Speech recognition study are interwoven with issues in Time delay neural network, Noise measurement, Segmentation and Signal-to-noise ratio. He studies Deep neural networks which is a part of Artificial intelligence.

The Recurrent neural network research Jun Du does as part of his general Artificial neural network study is frequently linked to other disciplines of science, such as Expression, therefore creating a link between diverse domains of science. As a part of the same scientific study, Jun Du usually deals with the Speech enhancement, concentrating on Minimum mean square error and frequently concerns with Equalization. His study in Pattern recognition is interdisciplinary in nature, drawing from both Encoder, Decoding methods and Speech processing.

His most cited work include:

  • A regression approach to speech enhancement based on deep neural networks (737 citations)
  • An Experimental Study on Speech Enhancement Based on Deep Neural Networks (562 citations)
  • Multiple-target deep learning for LSTM-RNN based speech enhancement (98 citations)

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

Jun Du focuses on Speech recognition, Artificial intelligence, Pattern recognition, Artificial neural network and Speech enhancement. His work on Speech recognition deals in particular with Word error rate, Hidden Markov model, Speaker diarisation, Voice activity detection and Speech processing. His study brings together the fields of Encoder and Artificial intelligence.

Jun Du combines subjects such as Recurrent neural network and Decoding methods with his study of Pattern recognition. He combines subjects such as Signal-to-noise ratio, Embedding, Feature and Regression with his study of Artificial neural network. His research in Speech enhancement intersects with topics in Intelligibility, Noise measurement and Minimum mean square error.

He most often published in these fields:

  • Speech recognition (63.38%)
  • Artificial intelligence (58.22%)
  • Pattern recognition (43.19%)

What were the highlights of his more recent work (between 2019-2021)?

  • Speech recognition (63.38%)
  • Artificial intelligence (58.22%)
  • Speech enhancement (27.23%)

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

His primary areas of study are Speech recognition, Artificial intelligence, Speech enhancement, Pattern recognition and Artificial neural network. His work on Speaker diarisation, Word error rate and Hidden Markov model as part of his general Speech recognition study is frequently connected to Task analysis, thereby bridging the divide between different branches of science. His research investigates the link between Artificial intelligence and topics such as Encoder that cross with problems in Visualization and Vocabulary.

His study in Speech enhancement is interdisciplinary in nature, drawing from both Intelligibility, Microphone array, Minimum mean square error and Separation. His Pattern recognition study combines topics in areas such as Convolution, Representation and Robustness. His work deals with themes such as Mean squared error, Algorithm, Regression and Flexibility, which intersect with Artificial neural network.

Between 2019 and 2021, his most popular works were:

  • Adaptive Period Embedding for Representing Oriented Objects in Aerial Images (16 citations)
  • On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression (15 citations)
  • Writer-aware CNN for parsimonious HMM-based offline handwritten Chinese text recognition (13 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

The scientist’s investigation covers issues in Speech recognition, Speaker diarisation, Artificial intelligence, Convolutional neural network and Speech enhancement. Many of his research projects under Speech recognition are closely connected to Task analysis with Task analysis, tying the diverse disciplines of science together. His Speaker diarisation study incorporates themes from Robustness and Voice activity detection.

Much of his study explores Artificial intelligence relationship to Pattern recognition. His Convolutional neural network research is multidisciplinary, relying on both Deep learning and Test set. Jun Du works mostly in the field of Speech enhancement, limiting it down to concerns involving Artificial neural network and, occasionally, Mean squared error and Contrast.

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 regression approach to speech enhancement based on deep neural networks

Yong Xu;Jun Du;Li-Rong Dai;Chin-Hui Lee.
IEEE Transactions on Audio, Speech, and Language Processing (2015)

995 Citations

An Experimental Study on Speech Enhancement Based on Deep Neural Networks

Yong Xu;Jun Du;Li-Rong Dai;Chin-Hui Lee.
IEEE Signal Processing Letters (2014)

774 Citations

Multiple-target deep learning for LSTM-RNN based speech enhancement

Lei Sun;Jun Du;Li-Rong Dai;Chin-Hui Lee.
2017 Hands-free Speech Communications and Microphone Arrays (HSCMA) (2017)

138 Citations

Robust speech recognition with speech enhanced deep neural networks.

Jun Du;Qing Wang;Tian Gao;Yong Xu.
conference of the international speech communication association (2014)

115 Citations

Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition

Jianshu Zhang;Jun Du;Shiliang Zhang;Dan Liu.
Pattern Recognition (2017)

110 Citations

Multi-objective learning and mask-based post-processing for deep neural network based speech enhancement.

Yong Xu;Jun Du;Zhen Huang;Li-Rong Dai.
conference of the international speech communication association (2015)

96 Citations

A speech enhancement approach using piecewise linear approximation of an explicit model of environmental distortions.

Jun Du;Qiang Huo.
conference of the international speech communication association (2008)

93 Citations

Dynamic noise aware training for speech enhancement based on deep neural networks.

Yong Xu;Jun Du;Li-Rong Dai;Chin-Hui Lee.
conference of the international speech communication association (2014)

86 Citations

A regression approach to single-channel speech separation via high-resolution deep neural networks

Jun Du;Yanhui Tu;Li-Rong Dai;Chin-Hui Lee.
IEEE Transactions on Audio, Speech, and Language Processing (2016)

77 Citations

Joint training of front-end and back-end deep neural networks for robust speech recognition

Tian Gao;Jun Du;Li-Rong Dai;Chin-Hui Lee.
international conference on acoustics, speech, and signal processing (2015)

76 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Jun Du

Yu Tsao

Yu Tsao

Center for Information Technology

Publications: 93

Shinji Watanabe

Shinji Watanabe

Carnegie Mellon University

Publications: 54

DeLiang Wang

DeLiang Wang

The Ohio State University

Publications: 49

Hsin-Min Wang

Hsin-Min Wang

Academia Sinica

Publications: 35

Chin-Hui Lee

Chin-Hui Lee

Georgia Institute of Technology

Publications: 29

Jinyu Li

Jinyu Li

Microsoft (United States)

Publications: 26

Dong Yu

Dong Yu

Tencent (China)

Publications: 26

Lianwen Jin

Lianwen Jin

South China University of Technology

Publications: 24

Takuya Yoshioka

Takuya Yoshioka

Microsoft (United States)

Publications: 20

Wenwu Wang

Wenwu Wang

University of Surrey

Publications: 20

Benoit Champagne

Benoit Champagne

McGill University

Publications: 19

Kuldip K. Paliwal

Kuldip K. Paliwal

Griffith University

Publications: 19

Tomohiro Nakatani

Tomohiro Nakatani

NTT (Japan)

Publications: 18

Lukas Burget

Lukas Burget

Brno University of Technology

Publications: 18

Emmanuel Vincent

Emmanuel Vincent

University of Lorraine

Publications: 18

Jesper Jensen

Jesper Jensen

Aalborg University

Publications: 18

Something went wrong. Please try again later.