World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8502
World Ranking
7551
National Ranking
451

Overview

Wenwu Wang is affiliated with the University of Surrey in the United Kingdom. Their primary research areas are within Computer Science, with a significant focus on Signal Processing, Artificial Intelligence, and Computer Vision and Pattern Recognition. Additional subfields include Electrical and Electronic Engineering and Computational Mechanics.

The main topics of Wenwu Wang's work encompass:

  • Music and Audio Processing
  • Speech and Audio Processing
  • Speech Recognition and Synthesis
  • Music Technology and Sound Studies
  • Video Analysis and Summarization
  • Anomaly Detection Techniques and Applications
  • Multimodal Machine Learning Applications

Wenwu Wang has contributed extensively to academic literature, with numerous publications appearing predominantly in the following venues:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • IEEE Signal Processing Letters
  • Zenodo (CERN European Organization for Nuclear Research)
  • 2022 30th European Signal Processing Conference (EUSIPCO)

Among recent papers authored or co-authored by Wenwu Wang are:

  • "PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition," 2020, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Sound Event Detection of Weakly Labelled Data With CNN-Transformer and Automatic Threshold Optimization," 2020, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Plastic damage prediction of concrete under compression based on deep learning," 2023, Acta Mechanica
  • "AudioLDM 2: Learning Holistic Audio Generation With Self-Supervised Pretraining," 2024, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research," 2024, IEEE/ACM Transactions on Audio Speech and Language Processing

Wenwu Wang's frequent collaborators include:

  • Mark D. Plumbley
  • Xubo Liu
  • Haohe Liu
  • Xinhao Mei
  • Qiuqiang Kong

The collective body of Wenwu Wang's research highlights a consistent focus on advancing technologies in audio and speech processing, machine learning applications in multimodal data, and signal processing methodologies alongside contributions to computational mechanics through deep learning approaches.

Best Publications

  • PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition

    Qiuqiang Kong;Yin Cao;Turab Iqbal;Yuxuan Wang

  • Large-Scale Weakly Supervised Audio Classification Using Gated Convolutional Neural Network

    Yong Xu;Qiuqiang Kong;Wenwu Wang;Mark D. Plumbley

  • AudioLDM: Text-to-Audio Generation with Latent Diffusion Models

    Unknown

  • Simultaneous Codeword Optimization (SimCO) for Dictionary Update and Learning

    Wei Dai;Tao Xu;Wenwu Wang

  • Sound Event Detection and Time–Frequency Segmentation from Weakly Labelled Data

    Qiuqiang Kong;Yong Xu;Iwona Sobieraj;Wenwu Wang

  • Heterogeneous Feature Selection With Multi-Modal Deep Neural Networks and Sparse Group LASSO

    Lei Zhao;Qinghua Hu;Wenwu Wang

  • Blind Source Separation

    Ganesh R. Naik;Wenwu Wang

  • Sound Event Detection of Weakly Labelled Data With CNN-Transformer and Automatic Threshold Optimization

    Qiuqiang Kong;Yong Xu;Wenwu Wang;Mark D. Plumbley

  • Polyphonic sound event detection and localization using a two-stage strategy

    Yin Cao;Qiuqiang Kong;Turab Iqbal;Fengyan An

  • Audio Set Classification with Attention Model: A Probabilistic Perspective

    Qiuqiang Kong;Yong Xu;Wenwu Wang;Mark D. Plumbley

  • Anomalous Sound Detection Using Spectral-Temporal Information Fusion

    Unknown

  • Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging

    Yong Xu;Qiang Huang;Wenwu Wang;Peter Foster

  • Convolutional gated recurrent neural network incorporating spatial features for audio tagging

    Yong Xu;Qiuqiang Kong;Qiang Huang;Wenwu Wang

  • Penalty function-based joint diagonalization approach for convolutive blind separation of nonstationary sources

    Wenwu Wang;S. Sanei;J.A. Chambers

  • Audio Assisted Robust Visual Tracking With Adaptive Particle Filtering

    Volkan Kilic;Mark Barnard;Wenwu Wang;Josef Kittler

  • Audiovisual Speech Source Separation: An overview of key methodologies

    Bertrand Rivet;Wenwu Wang;Syed Mohsen Naqvi;Jonathon A. Chambers

  • Video assisted speech source separation

    Wenwu Wang;D. Cosker;Y. Hicks;S. Saneit

  • Tensor dictionary learning with sparse TUCKER decomposition

    Syed Zubair;Wenwu Wang

  • Deep Neural Network Baseline for DCASE Challenge 2016

    Qiuqiang Kong;Iwona Sobieraj;Wenwu Wang;Mark Plumbley

  • A Multiplicative Algorithm for Convolutive Non-Negative Matrix Factorization Based on Squared Euclidean Distance

    Wenwu Wang;A. Cichocki;J.A. Chambers

  • Machine Audition: Principles, Algorithms and Systems

    Wenwu Wang

  • Variable step-size sign natural gradient algorithm for sequential blind source separation

    Lianxi Yuan;Wenwu Wang;J.A. Chambers

  • Weakly Labelled AudioSet Tagging with Attention Neural Networks

    Qiuqiang Kong;Changsong Yu;Turab Iqbal;Yong Xu

Frequent Co-Authors

Mark D. Plumbley
Mark D. Plumbley King's College London
Jonathon A. Chambers
Jonathon A. Chambers Harbin Engineering University
Saeid Sanei
Saeid Sanei Nottingham Trent University
Josef Kittler
Josef Kittler University of Surrey
Yuexian Zou
Yuexian Zou Peking University
Adrian Hilton
Adrian Hilton University of Surrey
Yuxuan Wang
Yuxuan Wang ByteDance
Qinghua Hu
Qinghua Hu Tianjin University
Francis Bach
Francis Bach École Normale Supérieure
Andrzej Cichocki
Andrzej Cichocki Systems Research Institute

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