World's Best Scientists 2026 revealed!
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Computer Science
China
2026

D-Index & Metrics

Computer Science

D-Index
98
Citations
34623
World Ranking
408
National Ranking
53

Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2004 - IEEE Fellow For contributions to advancing oscillatory correlation theory and its application to auditory and visual scene analysis.

Overview

DeLiang Wang is affiliated with The Ohio State University in the United States. Their research spans primarily the fields of Computer Science and Engineering, with significant contributions in subfields such as Signal Processing, Artificial Intelligence, Computational Mechanics, Cognitive Neuroscience, and Electrical and Electronic Engineering.

The main topics of their work focus heavily on Speech and Audio Processing, Speech Recognition and Synthesis, and Advanced Adaptive Filtering Techniques. Additional areas of research include Music and Audio Processing, Hearing Loss and Rehabilitation, Indoor and Outdoor Localization Technologies, and Acoustic Wave Phenomena Research.

DeLiang Wang has coauthored extensively with several collaborators, including Ashutosh Pandey, Heming Wang, Buye Xu, Hassan Taherian, and Zhong-Qiu Wang.

The scientist has published research in multiple reputable venues, notably:

  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • The Journal of the Acoustical Society of America
  • Interspeech 2022

Among recent publications are the following works:

  • Complex Spectral Mapping for Single- and Multi-Channel Speech Enhancement and Robust ASR (2020), IEEE/ACM Transactions on Audio Speech and Language Processing
  • Dense CNN With Self-Attention for Time-Domain Speech Enhancement (2021), IEEE/ACM Transactions on Audio Speech and Language Processing
  • Deep ANC: A deep learning approach to active noise control (2021), Neural Networks
  • Monaural Speech Dereverberation Using Temporal Convolutional Networks With Self Attention (2020), IEEE/ACM Transactions on Audio Speech and Language Processing
  • Multi-microphone Complex Spectral Mapping for Utterance-wise and Continuous Speech Separation (2021), IEEE/ACM Transactions on Audio Speech and Language Processing

DeLiang Wang was recognized as an IEEE Fellow in 2004 for contributions to advancing oscillatory correlation theory and its application to auditory and visual scene analysis.

Best Publications

  • Supervised Speech Separation Based on Deep Learning: An Overview

    DeLiang Wang;Jitong Chen

  • Computational Auditory Scene Analysis: Principles, Algorithms, and Applications

    DeLiang Wang;Guy J. Brown

  • On training targets for supervised speech separation

    Yuxuan Wang;Arun Narayanan;DeLiang Wang

  • Complex ratio masking for monaural speech separation

    Donald S. Williamson;Yuxuan Wang;DeLiang Wang

  • On Ideal Binary Mask As the Computational Goal of Auditory Scene Analysis

    DeLiang Wang

  • Ideal ratio mask estimation using deep neural networks for robust speech recognition

    Arun Narayanan;DeLiang Wang

  • Speech segregation based on sound localization

    Nicoleta Roman;DeLiang Wang;Guy J. Brown

  • Monaural speech segregation based on pitch tracking and amplitude modulation

    Guoning Hu;DeLiang Wang

  • Towards Scaling Up Classification-Based Speech Separation

    Yuxuan Wang;DeLiang Wang

  • The unimportance of phase in speech enhancement

    D. Wang;Jae Lim

  • Global competition and local cooperation in a network of neural oscillators

    David Terman;DeLiang Wang

  • Isolating the energetic component of speech-on-speech masking with ideal time-frequency segregation.

    Douglas S. Brungart;Peter S. Chang;Brian D. Simpson;DeLiang Wang

  • A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement.

    Ke Tan;DeLiang Wang

  • Image segmentation based on oscillatory correlation

    DeLiang Wang;David Terman

  • Separation of speech from interfering sounds based on oscillatory correlation

    DeLiang L. Wang;G.J. Brown

  • A multipitch tracking algorithm for noisy speech

    Mingyang Wu;DeLiang Wang;G.J. Brown

  • A Tandem Algorithm for Pitch Estimation and Voiced Speech Segregation

    Guoning Hu;DeLiang Wang

  • Locally excitatory globally inhibitory oscillator networks

    DeLiang Wang;D. Terman

  • TCNN: Temporal Convolutional Neural Network for Real-time Speech Enhancement in the Time Domain

    Ashutosh Pandey;DeLiang Wang

  • Learning Complex Spectral Mapping With Gated Convolutional Recurrent Networks for Monaural Speech Enhancement

    Ke Tan;DeLiang Wang

  • A multi-pitch tracking algorithm for noisy speech

    Mingyang Wu;DeLiang Wang;Guy J. Brown

  • MONAURAL SPEECH SEGREGATION BASED ON PITCH TRACKING AND

    Biophysics Program;DeLiang Wang

Frequent Co-Authors

Yuxuan Wang
Yuxuan Wang ByteDance
Guy J. Brown
Guy J. Brown University of Sheffield
Xiuwen Liu
Xiuwen Liu Florida State University
Michael A. Arbib
Michael A. Arbib University of Southern California
Jan Larsen
Jan Larsen Technical University of Denmark
Anuj Srivastava
Anuj Srivastava Florida State University
Ken Nakayama
Ken Nakayama Harvard University
John R. Hershey
John R. Hershey Google (United States)
Daniel P. W. Ellis
Daniel P. W. Ellis Google (United States)
Barbara G. Shinn-Cunningham
Barbara G. Shinn-Cunningham Carnegie Mellon University

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