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Person information
- affiliation: University of Surrey, Guildford, UK
- affiliation (2002 - 2014): Queen Mary University of London, UK
- affiliation (1991 - 2001): King's College London, UK
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2020 – today
- 2024
[j64]Francesco Renna
, Alex Gaudio, Sandra da Silva Mattos, Mark D. Plumbley, Miguel Tavares Coimbra:
Separation of the Aortic and Pulmonary Components of the Second Heart Sound via Alternating Optimization. IEEE Access 12: 34632-34643 (2024)- [j63]Yizhou Tan, Haojun Ai, Shengchen Li, Mark D. Plumbley:
Acoustic Scene Classification Across Cities and Devices via Feature Disentanglement. IEEE ACM Trans. Audio Speech Lang. Process. 32: 1286-1297 (2024) - [c190]Haohe Liu, Xubo Liu, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Learning Temporal Resolution in Spectrogram for Audio Classification. AAAI 2024: 13873-13881 - [i96]Jisheng Bai, Mou Wang, Haohe Liu, Han Yin, Yafei Jia, Siwei Huang, Yutong Du, Dongzhe Zhang, Dongyuan Shi, Woon-Seng Gan, Mark D. Plumbley, Susanto Rahardja, Bin Xiang, Jianfeng Chen:
Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift. CoRR abs/2402.02694 (2024) - 2023
- [j62]Zihang Song, Han Zhang, Sean Fuller, Andrew Lambert, Zhinong Ying, Petri Mähönen, Yonina C. Eldar, Shuguang Cui, Mark D. Plumbley, Clive Parini, Arumugam Nallanathan, Yue Gao:
Numerical evaluation on sub-Nyquist spectrum reconstruction methods. Frontiers Comput. Sci. 17(6): 176504 (2023) - [c189]Yi Yuan, Haohe Liu, Jinhua Liang, Xubo Liu, Mark D. Plumbley, Wenwu Wang:
Leveraging Pre-Trained AudioLDM for Sound Generation: A Benchmark Study. EUSIPCO 2023: 765-769 - [c188]Xubo Liu, Haohe Liu, Qiuqiang Kong, Xinhao Mei, Mark D. Plumbley, Wenwu Wang:
Simple Pooling Front-Ends for Efficient Audio Classification. ICASSP 2023: 1-5 - [c187]Arshdeep Singh, Mark D. Plumbley:
Efficient Similarity-Based Passive Filter Pruning for Compressing CNNS. ICASSP 2023: 1-5 - [c186]Haohe Liu, Zehua Chen, Yi Yuan, Xinhao Mei, Xubo Liu, Danilo P. Mandic, Wenwu Wang, Mark D. Plumbley:
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models. ICML 2023: 21450-21474 - [c185]James A. King, Arshdeep Singh, Mark D. Plumbley:
Compressing Audio CNNS with Graph Centrality Based Filter Pruning. WASPAA 2023: 1-5 - [i95]Haohe Liu, Zehua Chen, Yi Yuan, Xinhao Mei, Xubo Liu, Danilo P. Mandic, Wenwu Wang, Mark D. Plumbley:
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models. CoRR abs/2301.12503 (2023) - [i94]Yi Yuan, Haohe Liu, Jinhua Liang, Xubo Liu, Mark D. Plumbley, Wenwu Wang:
Leveraging Pre-trained AudioLDM for Text to Sound Generation: A Benchmark Study. CoRR abs/2303.03857 (2023) - [i93]Xinhao Mei, Chutong Meng, Haohe Liu, Qiuqiang Kong, Tom Ko, Chengqi Zhao, Mark D. Plumbley, Yuexian Zou, Wenwu Wang:
WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research. CoRR abs/2303.17395 (2023) - [i92]Arshdeep Singh, Mark D. Plumbley:
Efficient CNNs via Passive Filter Pruning. CoRR abs/2304.02319 (2023) - [i91]James A. King, Arshdeep Singh, Mark D. Plumbley:
Compressing audio CNNs with graph centrality based filter pruning. CoRR abs/2305.03391 (2023) - [i90]Qiuqiang Kong, Ke Chen, Haohe Liu, Xingjian Du, Taylor Berg-Kirkpatrick, Shlomo Dubnov, Mark D. Plumbley:
Universal Source Separation with Weakly Labelled Data. CoRR abs/2305.07447 (2023) - [i89]Yi Yuan, Haohe Liu, Xubo Liu, Xiyuan Kang, Mark D. Plumbley, Wenwu Wang:
Latent Diffusion Model Based Foley Sound Generation System For DCASE Challenge 2023 Task 7. CoRR abs/2305.15905 (2023) - [i88]Jinhua Liang, Xubo Liu, Haohe Liu, Huy Phan, Emmanouil Benetos, Mark D. Plumbley, Wenwu Wang:
Adapting Language-Audio Models as Few-Shot Audio Learners. CoRR abs/2305.17719 (2023) - [i87]Arshdeep Singh, Haohe Liu, Mark D. Plumbley:
E-PANNs: Sound Recognition Using Efficient Pre-trained Audio Neural Networks. CoRR abs/2305.18665 (2023) - [i86]Jianyuan Sun, Xubo Liu, Xinhao Mei, Volkan Kiliç, Mark D. Plumbley, Wenwu Wang:
Dual Transformer Decoder based Features Fusion Network for Automated Audio Captioning. CoRR abs/2305.18753 (2023) - [i85]Gabriel Bibbó, Arshdeep Singh, Mark D. Plumbley:
Audio Tagging on an Embedded Hardware Platform. CoRR abs/2306.09106 (2023) - [i84]Yi Yuan, Haohe Liu, Xubo Liu, Xiyuan Kang, Peipei Wu, Mark D. Plumbley, Wenwu Wang:
Text-Driven Foley Sound Generation With Latent Diffusion Model. CoRR abs/2306.10359 (2023) - [i83]Xubo Liu, Zhongkai Zhu, Haohe Liu, Yi Yuan, Meng Cui, Qiushi Huang, Jinhua Liang, Yin Cao, Qiuqiang Kong, Mark D. Plumbley, Wenwu Wang:
WavJourney: Compositional Audio Creation with Large Language Models. CoRR abs/2307.14335 (2023) - [i82]Xubo Liu, Qiuqiang Kong, Yan Zhao, Haohe Liu, Yi Yuan, Yuzhuo Liu, Rui Xia, Yuxuan Wang, Mark D. Plumbley, Wenwu Wang:
Separate Anything You Describe. CoRR abs/2308.05037 (2023) - [i81]Haohe Liu, Qiao Tian, Yi Yuan, Xubo Liu, Xinhao Mei, Qiuqiang Kong, Yuping Wang, Wenwu Wang, Yuxuan Wang, Mark D. Plumbley:
AudioLDM 2: Learning Holistic Audio Generation with Self-supervised Pretraining. CoRR abs/2308.05734 (2023) - [i80]Jinbo Hu, Yin Cao, Ming Wu, Feiran Yang, Ziying Yu, Wenwu Wang, Mark D. Plumbley, Jun Yang:
META-SELD: Meta-Learning for Fast Adaptation to the new environment in Sound Event Localization and Detection. CoRR abs/2308.08847 (2023) - [i79]Haohe Liu, Ke Chen, Qiao Tian, Wenwu Wang, Mark D. Plumbley:
AudioSR: Versatile Audio Super-resolution at Scale. CoRR abs/2309.07314 (2023) - [i78]Yi Yuan, Haohe Liu, Xubo Liu, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Retrieval-Augmented Text-to-Audio Generation. CoRR abs/2309.08051 (2023) - [i77]Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang:
Selective-Memory Meta-Learning with Environment Representations for Sound Event Localization and Detection. CoRR abs/2312.16422 (2023) - 2022
- [j61]Xinhao Mei, Xubo Liu, Mark D. Plumbley, Wenwu Wang:
Automated audio captioning: an overview of recent progress and new challenges. EURASIP J. Audio Speech Music. Process. 2022(1): 26 (2022) - [c184]Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang:
Sound Event Localization and Detection for Real Spatial Sound Scenes: Event-Independent Network and Data Augmentation Chains. DCASE 2022 - [c183]Haohe Liu, Xubo Liu, Xinhao Mei, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Segment-Level Metric Learning for Few-Shot Bioacoustic Event Detection. DCASE 2022 - [c182]Arshdeep Singh, Mark D. Plumbley:
Low-Complexity CNNs for Acoustic Scene Classification. DCASE 2022 - [c181]Yang Xiao, Xubo Liu, James A. King, Arshdeep Singh, Eng Siong Chng, Mark D. Plumbley, Wenwu Wang:
Continual Learning for On-Ddevice Environmental Sound Classification. DCASE 2022 - [c180]Jianyuan Sun, Xubo Liu, Xinhao Mei, Jinzheng Zhao, Mark D. Plumbley, Volkan Kiliç, Wenwu Wang:
Deep Neural Decision Forest for Acoustic Scene Classification. EUSIPCO 2022: 772-776 - [c179]Xubo Liu, Xinhao Mei, Qiushi Huang, Jianyuan Sun, Jinzheng Zhao, Haohe Liu, Mark D. Plumbley, Volkan Kilic, Wenwu Wang:
Leveraging Pre-trained BERT for Audio Captioning. EUSIPCO 2022: 1145-1149 - [c178]Xinhao Mei, Xubo Liu, Jianyuan Sun, Mark D. Plumbley, Wenwu Wang:
Diverse Audio Captioning Via Adversarial Training. ICASSP 2022: 8882-8886 - [c177]Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang:
A Track-Wise Ensemble Event Independent Network for Polyphonic Sound Event Localization and Detection. ICASSP 2022: 9196-9200 - [c176]Xubo Liu, Haohe Liu, Qiuqiang Kong, Xinhao Mei, Jinzheng Zhao, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Separate What You Describe: Language-Queried Audio Source Separation. INTERSPEECH 2022: 1801-1805 - [c175]Arshdeep Singh, Mark D. Plumbley:
A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification. INTERSPEECH 2022: 2433-2437 - [c174]Xinhao Mei, Xubo Liu, Jianyuan Sun, Mark D. Plumbley, Wenwu Wang:
On Metric Learning for Audio-Text Cross-Modal Retrieval. INTERSPEECH 2022: 4142-4146 - [c173]Meng Cui, Xubo Liu, Jinzheng Zhao, Jianyuan Sun, Guoping Lian, Tao Chen, Mark D. Plumbley, Daoliang Li, Wenwu Wang:
Fish Feeding Intensity Assessment in Aquaculture: A New Audio Dataset AFFIA3K and a Deep Learning Algorithm. MLSP 2022: 1-6 - [i76]Xubo Liu, Xinhao Mei, Qiushi Huang, Jianyuan Sun, Jinzheng Zhao, Haohe Liu, Mark D. Plumbley, Volkan Kiliç, Wenwu Wang:
Leveraging Pre-trained BERT for Audio Captioning. CoRR abs/2203.02838 (2022) - [i75]Jianyuan Sun, Xubo Liu, Xinhao Mei, Jinzheng Zhao, Mark D. Plumbley, Volkan Kiliç, Wenwu Wang:
Deep Neural Decision Forest for Acoustic Scene Classification. CoRR abs/2203.03436 (2022) - [i74]Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang:
A Track-Wise Ensemble Event Independent Network for Polyphonic Sound Event Localization and Detection. CoRR abs/2203.10228 (2022) - [i73]Xubo Liu, Haohe Liu, Qiuqiang Kong, Xinhao Mei, Jinzheng Zhao, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Separate What You Describe: Language-Queried Audio Source Separation. CoRR abs/2203.15147 (2022) - [i72]Xinhao Mei, Xubo Liu, Jianyuan Sun, Mark D. Plumbley, Wenwu Wang:
On Metric Learning for Audio-Text Cross-Modal Retrieval. CoRR abs/2203.15537 (2022) - [i71]Arshdeep Singh, Mark D. Plumbley:
A Passive Similarity based CNN Filter Pruning for Efficient Acoustic Scene Classification. CoRR abs/2203.15751 (2022) - [i70]Xinhao Mei, Xubo Liu, Mark D. Plumbley, Wenwu Wang:
Automated Audio Captioning: an Overview of Recent Progress and New Challenges. CoRR abs/2205.05949 (2022) - [i69]Yang Xiao, Xubo Liu, James A. King, Arshdeep Singh, Eng Siong Chng, Mark D. Plumbley, Wenwu Wang:
Continual Learning For On-Device Environmental Sound Classification. CoRR abs/2207.07429 (2022) - [i68]Haohe Liu, Xubo Liu, Xinhao Mei, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Segment-level Metric Learning for Few-shot Bioacoustic Event Detection. CoRR abs/2207.07773 (2022) - [i67]Haohe Liu, Xubo Liu, Xinhao Mei, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Surrey System for DCASE 2022 Task 5: Few-shot Bioacoustic Event Detection with Segment-level Metric Learning. CoRR abs/2207.10547 (2022) - [i66]Arshdeep Singh, Mark D. Plumbley:
Low-complexity CNNs for Acoustic Scene Classification. CoRR abs/2207.11529 (2022) - [i65]Arshdeep Singh, James A. King, Xubo Liu, Wenwu Wang, Mark D. Plumbley:
Low-complexity CNNs for Acoustic Scene Classification. CoRR abs/2208.01555 (2022) - [i64]Jinbo Hu, Yin Cao, Ming Wu, Qiuqiang Kong, Feiran Yang, Mark D. Plumbley, Jun Yang:
Sound Event Localization and Detection for Real Spatial Sound Scenes: Event-Independent Network and Data Augmentation Chains. CoRR abs/2209.01802 (2022) - [i63]Xubo Liu, Haohe Liu, Qiuqiang Kong, Xinhao Mei, Mark D. Plumbley, Wenwu Wang:
Simple Pooling Front-ends For Efficient Audio Classification. CoRR abs/2210.00943 (2022) - [i62]Haohe Liu, Xubo Liu, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Learning the Spectrogram Temporal Resolution for Audio Classification. CoRR abs/2210.01719 (2022) - [i61]Jianyuan Sun, Xubo Liu, Xinhao Mei, Mark D. Plumbley, Volkan Kilic, Wenwu Wang:
Automated Audio Captioning via Fusion of Low- and High- Dimensional Features. CoRR abs/2210.05037 (2022) - [i60]Xubo Liu, Qiushi Huang, Xinhao Mei, Haohe Liu, Qiuqiang Kong, Jianyuan Sun, Shengchen Li, Tom Ko, Yu Zhang, H. Lilian Tang, Mark D. Plumbley, Volkan Kiliç, Wenwu Wang:
Visually-Aware Audio Captioning With Adaptive Audio-Visual Attention. CoRR abs/2210.16428 (2022) - [i59]Arshdeep Singh, Mark D. Plumbley:
Efficient Similarity-based Passive Filter Pruning for Compressing CNNs. CoRR abs/2210.17416 (2022) - [i58]Haohe Liu, Qiuqiang Kong, Xubo Liu, Xinhao Mei, Wenwu Wang, Mark D. Plumbley:
Ontology-aware Learning and Evaluation for Audio Tagging. CoRR abs/2211.12195 (2022) - [i57]Sara Atito, Muhammad Awais, Wenwu Wang, Mark D. Plumbley, Josef Kittler:
ASiT: Audio Spectrogram vIsion Transformer for General Audio Representation. CoRR abs/2211.13189 (2022) - [i56]Xinhao Mei, Xubo Liu, Jianyuan Sun, Mark D. Plumbley, Wenwu Wang:
Towards Generating Diverse Audio Captions via Adversarial Training. CoRR abs/2212.02033 (2022) - 2021
- [j60]Yue Gao, Zihang Song, Han Zhang, Sean Fuller, Andrew Lambert, Zhinong Ying, Petri Mähönen, Yonina C. Eldar, Shuguang Cui, Mark D. Plumbley, Clive Parini, Arumugam Nallanathan:
Sub-Nyquist spectrum sensing and learning challenge. Frontiers Comput. Sci. 15(4): 154504 (2021) - [j59]Bin Li, Lucas Rencker, Jing Dong, Yuhui Luo, Mark D. Plumbley, Wenwu Wang:
Sparse Analysis Model Based Dictionary Learning for Signal Declipping. IEEE J. Sel. Top. Signal Process. 15(1): 25-36 (2021) - [j58]Annamaria Mesaros, Toni Heittola, Tuomas Virtanen, Mark D. Plumbley:
Sound Event Detection: A tutorial. IEEE Signal Process. Mag. 38(5): 67-83 (2021) - [j57]Jie Jiang, Qiuqiang Kong, Mark D. Plumbley, Nigel Gilbert, Mark Hoogendoorn, Diederik M. Roijers:
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances. ACM Trans. Knowl. Discov. Data 15(3): 50:1-50:21 (2021) - [j56]Zhao Ren, Qiuqiang Kong, Jing Han, Mark D. Plumbley, Björn W. Schuller:
CAA-Net: Conditional Atrous CNNs With Attention for Explainable Device-Robust Acoustic Scene Classification. IEEE Trans. Multim. 23: 4131-4142 (2021) - [c172]Francesco Renna, Mark D. Plumbley, Miguel T. Coimbra:
Source Separation of the Second Heart Sound via Alternating Optimization. CinC 2021: 1-4 - [c171]Andres Fernandez, Mark D. Plumbley:
Using UMAP to Inspect Audio Data for Unsupervised Anomaly Detection Under Domain-Shift Conditions. DCASE 2021: 165-169 - [c170]Xubo Liu, Qiushi Huang, Xinhao Mei, Tom Ko, H. Lilian Tang, Mark D. Plumbley, Wenwu Wang:
CL4AC: A Contrastive Loss for Audio Captioning. DCASE 2021: 196-200 - [c169]Turab Iqbal, Yin Cao, Andrew Bailey, Mark D. Plumbley, Wenwu Wang:
ARCA23K: An Audio Dataset for Investigating Open-Set Label Noise. DCASE 2021: 201-205 - [c168]Xinhao Mei, Qiushi Huang, Xubo Liu, Gengyun Chen, Jingqian Wu, Yusong Wu, Jinzheng Zhao, Shengchen Li, Tom Ko, H. Lilian Tang, Xi Shao, Mark D. Plumbley, Wenwu Wang:
An Encoder-Decoder Based Audio Captioning System with Transfer and Reinforcement Learning. DCASE 2021: 206-210 - [c167]Xinhao Mei, Xubo Liu, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Audio Captioning Transformer. DCASE 2021: 211-215 - [c166]Lam Pham, Chris Baume, Qiuqiang Kong, Tassadaq Hussain, Wenwu Wang, Mark D. Plumbley:
An Audio-Based Deep Learning Framework For BBC Television Programme Classification. EUSIPCO 2021: 56-60 - [c165]Andrew Bailey, Mark D. Plumbley:
Gender Bias in Depression Detection Using Audio Features. EUSIPCO 2021: 596-600 - [c164]Yin Cao, Turab Iqbal, Qiuqiang Kong, Fengyan An, Wenwu Wang, Mark D. Plumbley:
An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection. ICASSP 2021: 885-889 - [c163]Jingshu Zhang, Mark D. Plumbley, Wenwu Wang:
Weighted Magnitude-Phase Loss for Speech Dereverberation. ICASSP 2021: 5794-5798 - [c162]Xubo Liu, Turab Iqbal, Jinzheng Zhao, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Conditional Sound Generation Using Neural Discrete Time-Frequency Representation Learning. MLSP 2021: 1-6 - [i55]Lam Pham, Chris Baume, Qiuqiang Kong, Tassadaq Hussain, Wenwu Wang, Mark D. Plumbley:
An Audio-Based Deep Learning Framework ForBBC Television Programme Classification. CoRR abs/2104.01161 (2021) - [i54]Marc C. Green, Mark D. Plumbley:
Federated Learning With Highly Imbalanced Audio Data. CoRR abs/2105.08550 (2021) - [i53]Xinhao Mei, Xubo Liu, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Audio Captioning Transformer. CoRR abs/2107.09817 (2021) - [i52]Xubo Liu, Qiushi Huang, Xinhao Mei, Tom Ko, H. Lilian Tang, Mark D. Plumbley, Wenwu Wang:
CL4AC: A Contrastive Loss for Audio Captioning. CoRR abs/2107.09990 (2021) - [i51]Xubo Liu, Turab Iqbal, Jinzheng Zhao, Qiushi Huang, Mark D. Plumbley, Wenwu Wang:
Conditional Sound Generation Using Neural Discrete Time-Frequency Representation Learning. CoRR abs/2107.09998 (2021) - [i50]Andres Fernandez, Mark D. Plumbley:
Using UMAP to Inspect Audio Data for Unsupervised Anomaly Detection under Domain-Shift Conditions. CoRR abs/2107.10880 (2021) - [i49]Xinhao Mei, Qiushi Huang, Xubo Liu, Gengyun Chen, Jingqian Wu, Yusong Wu, Jinzheng Zhao, Shengchen Li, Tom Ko, H. Lilian Tang, Xi Shao, Mark D. Plumbley, Wenwu Wang:
An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement Learning. CoRR abs/2108.02752 (2021) - [i48]Turab Iqbal, Yin Cao, Andrew Bailey, Mark D. Plumbley, Wenwu Wang:
ARCA23K: An audio dataset for investigating open-set label noise. CoRR abs/2109.09227 (2021) - [i47]Xinhao Mei, Xubo Liu, Jianyuan Sun, Mark D. Plumbley, Wenwu Wang:
Diverse Audio Captioning via Adversarial Training. CoRR abs/2110.06691 (2021) - 2020
- [j55]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
Sound Event Detection of Weakly Labelled Data With CNN-Transformer and Automatic Threshold Optimization. IEEE ACM Trans. Audio Speech Lang. Process. 28: 2450-2460 (2020) - [j54]Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, Mark D. Plumbley:
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 28: 2880-2894 (2020) - [c161]Yin Cao, Turab Iqbal, Qiuqiang Kong, Yue Zhong, Wenwu Wang, Mark D. Plumbley:
Event-Independent Network for Polyphonic Sound Event Localization and Detection. DCASE 2020: 11-15 - [c160]Saeid Safavi, Turab Iqbal, Wenwu Wang, Philip Coleman, Mark D. Plumbley:
Open-Window: A Sound Event Dataset for Window State Detection and Recognition. DCASE 2020: 185-189 - [c159]Tomoya Koike, Kun Qian, Qiuqiang Kong, Mark D. Plumbley, Björn W. Schuller, Yoshiharu Yamamoto:
Audio for Audio is Better? An Investigation on Transfer Learning Models for Heart Sound Classification. EMBC 2020: 74-77 - [c158]Emad M. Grais, Fei Zhao, Mark D. Plumbley:
Multi-Band Multi-Resolution Fully Convolutional Neural Networks for Singing Voice Separation. EUSIPCO 2020: 261-265 - [c157]Qiuqiang Kong, Yuxuan Wang, Xuchen Song, Yin Cao, Wenwu Wang, Mark D. Plumbley:
Source Separation with Weakly Labelled Data: an Approach to Computational Auditory Scene Analysis. ICASSP 2020: 101-105 - [c156]Turab Iqbal, Yin Cao, Qiuqiang Kong, Mark D. Plumbley, Wenwu Wang:
Learning With Out-of-Distribution Data for Audio Classification. ICASSP 2020: 636-640 - [i46]Qiuqiang Kong, Yuxuan Wang, Xuchen Song, Yin Cao, Wenwu Wang, Mark D. Plumbley:
Source separation with weakly labelled data: An approach to computational auditory scene analysis. CoRR abs/2002.02065 (2020) - [i45]Turab Iqbal, Yin Cao, Qiuqiang Kong, Mark D. Plumbley, Wenwu Wang:
Learning with Out-of-Distribution Data for Audio Classification. CoRR abs/2002.04683 (2020) - [i44]Yin Cao, Turab Iqbal, Qiuqiang Kong, Yue Zhong, Wenwu Wang, Mark D. Plumbley:
Event-Independent Network for Polyphonic Sound Event Localization and Detection. CoRR abs/2010.00140 (2020) - [i43]Yin Cao, Turab Iqbal, Qiuqiang Kong, Fengyan An, Wenwu Wang, Mark D. Plumbley:
An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection. CoRR abs/2010.13092 (2020) - [i42]Andrew Bailey, Mark D. Plumbley:
Raw Audio for Depression Detection Can Be More Robust Against Gender Imbalance than Mel-Spectrogram Features. CoRR abs/2010.15120 (2020) - [i41]Zhao Ren, Qiuqiang Kong, Jing Han, Mark D. Plumbley, Björn W. Schuller:
CAA-Net: Conditional Atrous CNNs with Attention for Explainable Device-robust Acoustic Scene Classification. CoRR abs/2011.09299 (2020)
2010 – 2019
- 2019
- [j53]Estefanía Cano, Derry FitzGerald, Antoine Liutkus, Mark D. Plumbley, Fabian-Robert Stöter:
Musical Source Separation: An Introduction. IEEE Signal Process. Mag. 36(1): 31-40 (2019) - [j52]Qiuqiang Kong, Yong Xu, Iwona Sobieraj, Wenwu Wang, Mark D. Plumbley:
Sound Event Detection and Time-Frequency Segmentation from Weakly Labelled Data. IEEE ACM Trans. Audio Speech Lang. Process. 27(4): 777-787 (2019) - [j51]Qiuqiang Kong, Changsong Yu, Yong Xu, Turab Iqbal, Wenwu Wang, Mark D. Plumbley:
Weakly Labelled AudioSet Tagging With Attention Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 27(11): 1791-1802 (2019) - [j50]Lucas Rencker, Francis R. Bach, Wenwu Wang, Mark D. Plumbley:
Sparse Recovery and Dictionary Learning From Nonlinear Compressive Measurements. IEEE Trans. Signal Process. 67(21): 5659-5670 (2019) - [c155]Yin Cao, Qiuqiang Kong, Turab Iqbal, Fengyan An, Wenwu Wang, Mark D. Plumbley:
Polyphonic Sound Event Detection and Localization using a Two-Stage Strategy. DCASE 2019: 30-34 - [c154]François Grondin, Iwona Sobieraj, Mark D. Plumbley, James R. Glass:
Sound Event Localization and Detection Using CRNN on Pairs of Microphones. DCASE 2019: 84-88 - [c153]Zhao Ren, Jing Han, Nicholas Cummins, Qiuqiang Kong, Mark D. Plumbley, Björn W. Schuller:
Multi-instance Learning for Bipolar Disorder Diagnosis using Weakly Labelled Speech Data. PDH 2019: 79-83 - [c152]Emad M. Grais, Hagen Wierstorf, Dominic Ward, Russell Mason, Mark D. Plumbley:
Referenceless Performance Evaluation of Audio Source Separation using Deep Neural Networks. EUSIPCO 2019: 1-5 - [c151]Zuzanna Podwinska, Iwona Sobieraj, Bruno M. Fazenda, William J. Davies, Mark D. Plumbley:
Acoustic Event Detection from Weakly Labeled Data Using Auditory Salience. ICASSP 2019: 41-45 - [c150]Yuanbo Hou, Qiuqiang Kong, Shengchen Li, Mark D. Plumbley:
Sound Event Detection with Sequentially Labelled Data Based on Connectionist Temporal Classification and Unsupervised Clustering. ICASSP 2019: 46-50 - [c149]Zhao Ren, Qiuqiang Kong, Jing Han, Mark D. Plumbley, Björn W. Schuller:
Attention-based Atrous Convolutional Neural Networks: Visualisation and Understanding Perspectives of Acoustic Scenes. ICASSP 2019: 56-60 - [c148]Qiuqiang Kong, Yong Xu, Turab Iqbal, Yin Cao, Wenwu Wang, Mark D. Plumbley:
Acoustic Scene Generation with Conditional Samplernn. ICASSP 2019: 925-929 - [c147]Christian Kroos, Oliver Bones, Yin Cao, Lara Harris, Philip J. B. Jackson, William J. Davies, Wenwu Wang, Trevor J. Cox, Mark D. Plumbley:
Generalisation in Environmental Sound Classification: The 'Making Sense of Sounds' Data Set and Challenge. ICASSP 2019: 8082-8086 - [c146]Qiuqiang Kong, Yong Xu, Philip J. B. Jackson, Wenwu Wang, Mark D. Plumbley:
Single-Channel Signal Separation and Deconvolution with Generative Adversarial Networks. IJCAI 2019: 2747-2753 - [i40]Qiuqiang Kong, Changsong Yu, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley:
Weakly labelled AudioSet Classification with Attention Neural Networks. CoRR abs/1903.00765 (2019) - [i39]Qiuqiang Kong, Yin Cao, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley:
Cross-task learning for audio tagging, sound event detection and spatial localization: DCASE 2019 baseline systems. CoRR abs/1904.03476 (2019) - [i38]Yuanbo Hou, Qiuqiang Kong, Shengchen Li, Mark D. Plumbley:
Sound Event Detection with Sequentially Labelled Data Based on Connectionist Temporal Classification and Unsupervised Clustering. CoRR abs/1904.12102 (2019) - [i37]Yin Cao, Qiuqiang Kong, Turab Iqbal, Fengyan An, Wenwu Wang, Mark D. Plumbley:
Polyphonic Sound Event Detection and Localization using a Two-Stage Strategy. CoRR abs/1905.00268 (2019) - [i36]Qiuqiang Kong, Yong Xu, Wenwu Wang, Philip J. B. Jackson, Mark D. Plumbley:
Single-Channel Signal Separation and Deconvolution with Generative Adversarial Networks. CoRR abs/1906.07552 (2019) - [i35]Jie Jiang, Qiuqiang Kong, Mark D. Plumbley, Nigel Gilbert:
Deep Learning Based Energy Disaggregation and On/Off Detection of Household Appliances. CoRR abs/1908.00941 (2019) - [i34]Emad M. Grais, Fei Zhao, Mark D. Plumbley:
Multi-Band Multi-Resolution Fully Convolutional Neural Networks for Singing Voice Separation. CoRR abs/1910.09266 (2019) - [i33]François Grondin, James R. Glass, Iwona Sobieraj, Mark D. Plumbley:
Sound Event Localization and Detection Using CRNN on Pairs of Microphones. CoRR abs/1910.10049 (2019) - [i32]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
Sound Event Detection of Weakly Labelled Data with CNN-Transformer and Automatic Threshold Optimization. CoRR abs/1912.04761 (2019) - [i31]Qiuqiang Kong, Yin Cao, Turab Iqbal, Yuxuan Wang, Wenwu Wang, Mark D. Plumbley:
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition. CoRR abs/1912.10211 (2019) - 2018
- [j49]Chris Baume, Mark D. Plumbley, Janko Calic, David M. Frohlich:
A Contextual Study of Semantic Speech Editing in Radio Production. Int. J. Hum. Comput. Stud. 115: 67-80 (2018) - [j48]Annamaria Mesaros, Toni Heittola, Emmanouil Benetos, Peter Foster, Mathieu Lagrange, Tuomas Virtanen, Mark D. Plumbley:
Detection and Classification of Acoustic Scenes and Events: Outcome of the DCASE 2016 Challenge. IEEE ACM Trans. Audio Speech Lang. Process. 26(2): 379-393 (2018) - [j47]Zhijin Qin, Yue Gao, Mark D. Plumbley:
Malicious User Detection Based on Low-Rank Matrix Completion in Wideband Spectrum Sensing. IEEE Trans. Signal Process. 66(1): 5-17 (2018) - [c145]Saeid Safavi, Andy Pearce, Wenwu Wang, Mark D. Plumbley:
Predicting the perceived level of reverberation using machine learning. ACSSC 2018: 27-30 - [c144]Zhao Ren, Qiuqiang Kong, Kun Qian, Mark D. Plumbley, Björn W. Schuller:
Attention-based convolutional neural networks for acoustic scene classification. DCASE 2018: 39-43 - [c143]Turab Iqbal, Qiuqiang Kong, Mark D. Plumbley, Wenwu Wang:
General-purpose audio tagging from noisy labels using convolutional neural networks. DCASE 2018: 212-216 - [c142]Qiuqiang Kong, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley:
DCASE 2018 Challenge Surrey cross-task convolutional neural network baseline. DCASE 2018: 217-221 - [c141]Emad M. Grais, Dominic Ward, Mark D. Plumbley:
Raw Multi-Channel Audio Source Separation using Multi- Resolution Convolutional Auto-Encoders. EUSIPCO 2018: 1577-1581 - [c140]Cian O'Brien, Mark D. Plumbley:
A Hierarchical Latent Mixture Model for Polyphonic Music Analysis. EUSIPCO 2018: 1910-1914 - [c139]Tijs Duel, David M. Frohlich, Christian Kroos, Yong Xu, Philip J. B. Jackson, Mark D. Plumbley:
Supporting Audiography: Design of a System for Sentimental Sound Recording, Classification and Playback. HCI (28) 2018: 24-31 - [c138]Emad M. Grais, Hagen Wierstorf, Dominic Ward, Mark D. Plumbley:
Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation. LVA/ICA 2018: 340-350 - [c137]Alfredo Zermini, Qiuqiang Kong, Yong Xu, Mark D. Plumbley, Wenwu Wang:
Improving Reverberant Speech Separation with Binaural Cues Using Temporal Context and Convolutional Neural Networks. LVA/ICA 2018: 361-371 - [c136]Lucas Rencker, Francis R. Bach, Wenwu Wang, Mark D. Plumbley:
Consistent Dictionary Learning for Signal Declipping. LVA/ICA 2018: 446-455 - [c135]Yong Xu, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Large-Scale Weakly Supervised Audio Classification Using Gated Convolutional Neural Network. ICASSP 2018: 121-125 - [c134]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
Audio Set Classification with Attention Model: A Probabilistic Perspective. ICASSP 2018: 316-320 - [c133]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
A Joint Separation-Classification Model for Sound Event Detection of Weakly Labelled Data. ICASSP 2018: 321-325 - [c132]Dominic Ward, Hagen Wierstorf, Russell D. Mason, Emad M. Grais, Mark D. Plumbley:
BSS Eval or Peass? Predicting the Perception of Singing-Voice Separation. ICASSP 2018: 596-600 - [c131]Qiang Huang, Philip J. B. Jackson, Mark D. Plumbley, Wenwu Wang:
Synthesis of Images by Two-Stage Generative Adversarial Networks. ICASSP 2018: 1593-1597 - [c130]Iwona Sobieraj, Lucas Rencker, Mark D. Plumbley:
Orthogonality-Regularized Masked NMF for Learning on Weakly Labeled Audio Data. ICASSP 2018: 2436-2440 - [c129]Cian O'Brien, Mark D. Plumbley:
Inexact Proximal Operators for 𝓁p-Quasinorm Minimization. ICASSP 2018: 4724-4728 - [e4]Mark D. Plumbley, Christian Kroos, Juan Pablo Bello, Gaël Richard, Daniel P. W. Ellis, Annamaria Mesaros:
Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2018, Surrey, UK, November 19-20, 2018. 2018, ISBN 978-952-15-4262-6 [contents] - [e3]Yannick Deville, Sharon Gannot, Russell Mason, Mark D. Plumbley, Dominic Ward:
Latent Variable Analysis and Signal Separation - 14th International Conference, LVA/ICA 2018, Guildford, UK, July 2-5, 2018, Proceedings. Lecture Notes in Computer Science 10891, Springer 2018, ISBN 978-3-319-93763-2 [contents] - [i30]Emad M. Grais, Dominic Ward, Mark D. Plumbley:
Raw Multi-Channel Audio Source Separation using Multi-Resolution Convolutional Auto-Encoders. CoRR abs/1803.00702 (2018) - [i29]Qiuqiang Kong, Yong Xu, Iwona Sobieraj, Wenwu Wang, Mark D. Plumbley:
Sound Event Detection and Time-Frequency Segmentation from Weakly Labelled Data. CoRR abs/1804.04715 (2018) - [i28]Qiuqiang Kong, Turab Iqbal, Yong Xu, Wenwu Wang, Mark D. Plumbley:
DCASE 2018 Challenge baseline with convolutional neural networks. CoRR abs/1808.00773 (2018) - [i27]Emad M. Grais, Hagen Wierstorf, Dominic Ward, Russell Mason, Mark D. Plumbley:
Referenceless Performance Evaluation of Audio Source Separation using Deep Neural Networks. CoRR abs/1811.00454 (2018) - 2017
- [j46]Yong Xu, Qiang Huang, Wenwu Wang, Peter Foster, Siddharth Sigtia, Philip J. B. Jackson, Mark D. Plumbley:
Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging. IEEE ACM Trans. Audio Speech Lang. Process. 25(6): 1230-1241 (2017) - [j45]Emmanouil Benetos, Grégoire Lafay, Mathieu Lagrange, Mark D. Plumbley:
Polyphonic Sound Event Tracking Using Linear Dynamical Systems. IEEE ACM Trans. Audio Speech Lang. Process. 25(6): 1266-1277 (2017) - [j44]Emad M. Grais, Gerard Roma, Andrew J. R. Simpson, Mark D. Plumbley:
Two-Stage Single-Channel Audio Source Separation Using Deep Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 25(9): 1773-1783 (2017) - [c128]Christian Kroos, Rikke L. Bundgaard-Nielsen, Catherine T. Best, Mark D. Plumbley:
Using deep neural networks to estimate tongue movements from speech face motion. AVSP 2017: 30-35 - [c127]Christian Kroos, Mark D. Plumbley:
Neuroevolution for Sound Event Detection in Real Life Audio: A Pilot Study. DCASE 2017: 64-68 - [c126]Qiuqiang Kong, Yong Xu, Mark D. Plumbley:
Joint detection and classification convolutional neural network on weakly labelled bird audio detection. EUSIPCO 2017: 1749-1753 - [c125]Iwona Sobieraj, Qiuqiang Kong, Mark D. Plumbley:
Masked non-negative matrix factorization for eire detection using weakly labeled data. EUSIPCO 2017: 1769-1773 - [c124]Cian O'Brien, Mark D. Plumbley:
Automatic music transcription using low rank non-negative matrix decomposition. EUSIPCO 2017: 1848-1852 - [c123]Lucas Rencker, Wenwu Wang, Mark D. Plumbley:
Multivariate iterative hard thresholding for sparse decomposition with flexible sparsity patterns. EUSIPCO 2017: 2156-2160 - [c122]Emad M. Grais, Mark D. Plumbley:
Single channel audio source separation using convolutional denoising autoencoders. GlobalSIP 2017: 1265-1269 - [c121]Andrew J. R. Simpson, Gerard Roma, Emad M. Grais, Russell D. Mason, Christopher Hummersone, Mark D. Plumbley:
Psychophysical Evaluation of Audio Source Separation Methods. LVA/ICA 2017: 211-221 - [c120]Emad M. Grais, Gerard Roma, Andrew J. R. Simpson, Mark D. Plumbley:
Discriminative Enhancement for Single Channel Audio Source Separation Using Deep Neural Networks. LVA/ICA 2017: 236-246 - [c119]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
A joint detection-classification model for audio tagging of weakly labelled data. ICASSP 2017: 641-645 - [c118]Ronan Hamon, Valentin Emiya, Lucas Rencker, Wenwu Wang, Mark D. Plumbley:
Assessment of musical noise using localization of isolated peaks in time-frequency domain. ICASSP 2017: 696-700 - [c117]Qiang Huang, Yong Xu, Philip J. B. Jackson, Wenwu Wang, Mark D. Plumbley:
Fast tagging of natural sounds using marginal co-regularization. ICASSP 2017: 2991-2995 - [c116]Lucas Rencker, Wenwu Wang, Mark D. Plumbley:
A greedy algorithm with learned statistics for sparse signal reconstruction. ICASSP 2017: 4775-4779 - [c115]Yong Xu, Qiuqiang Kong, Qiang Huang, Wenwu Wang, Mark D. Plumbley:
Convolutional gated recurrent neural network incorporating spatial features for audio tagging. IJCNN 2017: 3461-3466 - [c114]Christian Kroos, Mark D. Plumbley:
Learning the Mapping Function from Voltage Amplitudes to Sensor Positions in 3D-EMA Using Deep Neural Networks. INTERSPEECH 2017: 454-458 - [c113]Yong Xu, Qiuqiang Kong, Qiang Huang, Wenwu Wang, Mark D. Plumbley:
Attention and Localization Based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging. INTERSPEECH 2017: 3083-3087 - [c112]Shengchen Li, Simon Dixon, Mark D. Plumbley:
Clustering Expressive Timing with Regressed Polynomial Coefficients Demonstrated by a Model Selection Test. ISMIR 2017: 457-463 - [c111]Alfredo Zermini, Qingju Liu, Yong Xu, Mark D. Plumbley, Dave Betts, Wenwu Wang:
Binaural and log-power spectra features with deep neural networks for speech-noise separation. MMSP 2017: 1-6 - [i26]Yong Xu, Qiuqiang Kong, Qiang Huang, Wenwu Wang, Mark D. Plumbley:
Convolutional Gated Recurrent Neural Network Incorporating Spatial Features for Audio Tagging. CoRR abs/1702.07787 (2017) - [i25]Yong Xu, Qiuqiang Kong, Qiang Huang, Wenwu Wang, Mark D. Plumbley:
Attention and Localization based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging. CoRR abs/1703.06052 (2017) - [i24]Emad M. Grais, Mark D. Plumbley:
Single Channel Audio Source Separation using Convolutional Denoising Autoencoders. CoRR abs/1703.08019 (2017) - [i23]Yong Xu, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Surrey-cvssp system for DCASE2017 challenge task4. CoRR abs/1709.00551 (2017) - [i22]Yong Xu, Qiuqiang Kong, Wenwu Wang, Mark D. Plumbley:
Large-scale weakly supervised audio classification using gated convolutional neural network. CoRR abs/1710.00343 (2017) - [i21]Emad M. Grais, Hagen Wierstorf, Dominic Ward, Mark D. Plumbley:
Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation. CoRR abs/1710.11473 (2017) - [i20]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
Audio Set classification with attention model: A probabilistic perspective. CoRR abs/1711.00927 (2017) - [i19]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
A joint separation-classification model for sound event detection of weakly labelled data. CoRR abs/1711.03037 (2017) - 2016
- [j43]Ken O'Hanlon, Hidehisa Nagano, Nicolas Keriven, Mark D. Plumbley:
Non-Negative Group Sparsity with Subspace Note Modelling for Polyphonic Transcription. IEEE ACM Trans. Audio Speech Lang. Process. 24(3): 530-542 (2016) - [j42]Siddharth Sigtia, Adam M. Stark, Sacha Krstulovic, Mark D. Plumbley:
Automatic Environmental Sound Recognition: Performance Versus Computational Cost. IEEE ACM Trans. Audio Speech Lang. Process. 24(11): 2096-2107 (2016) - [j41]Jing Dong, Wenwu Wang, Wei Dai, Mark D. Plumbley, Zi-Fa Han, Jonathon A. Chambers:
Analysis SimCO Algorithms for Sparse Analysis Model Based Dictionary Learning. IEEE Trans. Signal Process. 64(2): 417-431 (2016) - [j40]Zhijin Qin, Yue Gao, Mark D. Plumbley, Clive G. Parini:
Wideband Spectrum Sensing on Real-Time Signals at Sub-Nyquist Sampling Rates in Single and Cooperative Multiple Nodes. IEEE Trans. Signal Process. 64(12): 3106-3117 (2016) - [c110]Qiuqiang Kong, Iwona Sobieraj, Wenwu Wang, Mark D. Plumbley:
Deep Neural Network Baseline for DCASE Challenge 2016. DCASE 2016: 50-54 - [c109]Iwona Sobieraj, Mark D. Plumbley:
Coupled Sparse NMF vs. Random Forest Classification for Real Life Acoustic Event Detection. DCASE 2016: 90-94 - [c108]Yong Xu, Qiang Huang, Wenwu Wang, Philip J. B. Jackson, Mark D. Plumbley:
Fully DNN-Based Multi-Label Regression for Audio Tagging. DCASE 2016: 105-109 - [c107]Yong Xu, Qiang Huang, Wenwu Wang, Mark D. Plumbley:
Hierarchical Learning for DNN-Based Acoustic Scene Classification. DCASE 2016: 110-114 - [c106]Andrew J. R. Simpson, Gerard Roma, Emad M. Grais, Russell D. Mason, Chris Hummersone, Antoine Liutkus, Mark D. Plumbley:
Evaluation of audio source separation models using hypothesis-driven non-parametric statistical methods. EUSIPCO 2016: 1763-1767 - [c105]Emmanouil Benetos, Grégoire Lafay, Mathieu Lagrange, Mark D. Plumbley:
Detection of overlapping acoustic events using a temporally-constrained probabilistic model. ICASSP 2016: 6450-6454 - [c104]Emad M. Grais, Gerard Roma, Andrew J. R. Simpson, Mark D. Plumbley:
Combining Mask Estimates for Single Channel Audio Source Separation Using Deep Neural Networks. INTERSPEECH 2016: 3339-3343 - [e2]Tuomas Virtanen, Annamaria Mesaros, Toni Heittola, Mark D. Plumbley, Peter Foster, Emmanouil Benetos, Mathieu Lagrange:
Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2016, Budapest, Hungary, September 3, 2016. 2016, ISBN 978-952-15-3807-0 [contents] - [i18]Yong Xu, Qiang Huang, Wenwu Wang, Philip J. B. Jackson, Mark D. Plumbley:
Fully DNN-based Multi-label regression for audio tagging. CoRR abs/1606.07695 (2016) - [i17]Yong Xu, Qiang Huang, Wenwu Wang, Peter Foster, Siddharth Sigtia, Philip J. B. Jackson, Mark D. Plumbley:
Fully Deep Neural Networks Incorporating Unsupervised Feature Learning for Audio Tagging. CoRR abs/1607.03681 (2016) - [i16]Yong Xu, Qiang Huang, Wenwu Wang, Mark D. Plumbley:
Hierachical learning for DNN-based acoustic scene classification. CoRR abs/1607.03682 (2016) - [i15]Siddharth Sigtia, Adam M. Stark, Sacha Krstulovic, Mark D. Plumbley:
Automatic Environmental Sound Recognition: Performance versus Computational Cost. CoRR abs/1607.04589 (2016) - [i14]Emad M. Grais, Gerard Roma, Andrew J. R. Simpson, Mark D. Plumbley:
Discriminative Enhancement for Single Channel Audio Source Separation using Deep Neural Networks. CoRR abs/1609.01678 (2016) - [i13]Qiuqiang Kong, Yong Xu, Wenwu Wang, Mark D. Plumbley:
A Joint Detection-Classification Model for Audio Tagging of Weakly Labelled Data. CoRR abs/1610.01797 (2016) - 2015
- [j39]Daniele Barchiesi, Dimitrios Giannoulis, Dan Stowell, Mark D. Plumbley:
Acoustic Scene Classification: Classifying environments from the sounds they produce. IEEE Signal Process. Mag. 32(3): 16-34 (2015) - [j38]Dan Stowell, Dimitrios Giannoulis, Emmanouil Benetos, Mathieu Lagrange, Mark D. Plumbley:
Detection and Classification of Acoustic Scenes and Events. IEEE Trans. Multim. 17(10): 1733-1746 (2015) - [j37]Daniele Barchiesi, Mark D. Plumbley:
Learning Incoherent Subspaces: Classification via Incoherent Dictionary Learning. J. Signal Process. Syst. 79(2): 189-199 (2015) - [c103]Shengchen Li, Dawn A. A. Black, Mark D. Plumbley:
The Clustering of Expressive Timing Within a Phrase in Classical Piano Performances by Gaussian Mixture Models. CMMR 2015: 322-345 - [c102]Andrew J. R. Simpson, Gerard Roma, Mark D. Plumbley:
Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network. LVA/ICA 2015: 429-436 - [c101]Sebastian Ewert, Mark D. Plumbley, Mark B. Sandler:
A dynamic programming variant of non-negative matrix deconvolution for the transcription of struck string instruments. ICASSP 2015: 569-573 - [c100]Ken O'Hanlon, Mark B. Sandler, Mark D. Plumbley:
Non-negative matrix factorisation incorporating greedy hellinger sparse coding applied to polyphonic music transcription. ICASSP 2015: 2214-2218 - [c99]Peter Foster, Siddharth Sigtia, Sacha Krstulovic, Jon Barker, Mark D. Plumbley:
Chime-home: A dataset for sound source recognition in a domestic environment. WASPAA 2015: 1-5 - [c98]Nima Mesgarani, Mark D. Plumbley:
Keynote addresses: Reverse engineering the neural mechanisms involved in robust speech processing. WASPAA 2015: 5 - [i12]Andrew J. R. Simpson, Gerard Roma, Mark D. Plumbley:
Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network. CoRR abs/1504.04658 (2015) - [i11]Andrew J. R. Simpson, Gerard Roma, Mark D. Plumbley:
Deep Remix: Remixing Musical Mixtures Using a Convolutional Deep Neural Network. CoRR abs/1505.00289 (2015) - 2014
- [j36]Sebastian Ewert, Bryan Pardo, Meinard Müller, Mark D. Plumbley:
Score-Informed Source Separation for Musical Audio Recordings: An overview. IEEE Signal Process. Mag. 31(3): 116-124 (2014) - [j35]Roland Badeau, Mark D. Plumbley:
Multichannel High-Resolution NMF for Modeling Convolutive Mixtures of Non-Stationary Signals in the Time-Frequency Domain. IEEE ACM Trans. Audio Speech Lang. Process. 22(11): 1670-1680 (2014) - [c97]Dan Stowell, Mark D. Plumbley:
Audio-only Bird Classification Using Unsupervised Feature Learning. CLEF (Working Notes) 2014: 673-684 - [c96]Zhijin Qin, Yue Gao, Mark D. Plumbley, Clive G. Parini, Laurie G. Cuthbert:
Efficient compressive spectrum sensing algorithm for M2M devices. GlobalSIP 2014: 1170-1174 - [c95]Sebastian Ewert, Mark D. Plumbley, Mark B. Sandler:
Accounting for phase cancellations in non-negative matrix factorization using weighted distances. ICASSP 2014: 649-653 - [c94]Ken O'Hanlon, Mark D. Plumbley:
Polyphonic piano transcription using non-negative Matrix Factorisation with group sparsity. ICASSP 2014: 3112-3116 - [c93]Dimitrios Giannoulis, Emmanouil Benetos, Anssi Klapuri, Mark D. Plumbley:
Improving instrument recognition in polyphonic music through system integration. ICASSP 2014: 5222-5226 - [c92]Estefanía Cano, Mark D. Plumbley, Christian Dittmar:
Phase-based harmonic/percussive separation. INTERSPEECH 2014: 1628-1632 - [c91]Tillman Weyde, Stephen Cottrell, Jason Dykes, Emmanouil Benetos, Daniel Wolff, Dan Tidhar, Alexander Kachkaev, Mark D. Plumbley, Simon Dixon, Mathieu Barthet, Nicolas Gold, Samer A. Abdallah, Aquiles Alancar-Brayner, Mahendra Mahey, Adam Tovell:
Big Data for Musicology. DLfM@JCDL 2014: 1-3 - [c90]Tim Murray Browne, Mark D. Plumbley:
Harmonic Motion: A Toolkit for Processing Gestural Data for Interactive Sound. NIME 2014: 213-216 - [c89]Dan Stowell, Mark D. Plumbley:
An Open Dataset for Research on Audio Field Recording Archives: freefield1010. Semantic Audio 2014 - [i10]Dan Stowell, Mark D. Plumbley:
Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning. CoRR abs/1405.6524 (2014) - [i9]Daniele Barchiesi, Dimitrios Giannoulis, Dan Stowell, Mark D. Plumbley:
Acoustic Scene Classification. CoRR abs/1411.3715 (2014) - 2013
- [j34]Andrew Robertson, Mark D. Plumbley:
Synchronizing Sequencing Software to a Live Drummer. Comput. Music. J. 37(2): 46-60 (2013) - [j33]Dan Stowell, Mark D. Plumbley:
Segregating event streams and noise with a Markov renewal process model. J. Mach. Learn. Res. 14(1): 2213-2238 (2013) - [j32]Bob L. Sturm, Boris Mailhé, Mark D. Plumbley:
On Theorem 10 in "On Polar Polytopes and the Recovery of Sparse Representations" [Sep 07 3188-3195]. IEEE Trans. Inf. Theory 59(8): 5206-5209 (2013) - [j31]Daniele Barchiesi, Mark D. Plumbley:
Learning Incoherent Dictionaries for Sparse Approximation Using Iterative Projections and Rotations. IEEE Trans. Signal Process. 61(8): 2055-2065 (2013) - [c88]Roland Badeau, Mark D. Plumbley:
Probabilistic time-frequency source-filter decomposition of non-stationary signals. EUSIPCO 2013: 1-5 - [c87]Dimitrios Giannoulis, Dan Stowell, Emmanouil Benetos, Mathias Rossignol, Mathieu Lagrange, Mark D. Plumbley:
A database and challenge for acoustic scene classification and event detection. EUSIPCO 2013: 1-5 - [c86]Boris Mailhé, Mark D. Plumbley:
Dictionary learning via projected maximal exploration. GlobalSIP 2013: 626 - [c85]Ken O'Hanlon, Mark D. Plumbley:
Learning overcomplete dictionaries with ℓ0-sparse Non-negative Matrix Factorisation. GlobalSIP 2013: 977-980 - [c84]Zhijin Qin, Yue Gao, Mark D. Plumbley, Clive Parini, Laurie G. Cuthbert:
Low-rank matrix completion based malicious user detection in cooperative spectrum sensing. GlobalSIP 2013: 1186-1189 - [c83]Samer A. Abdallah, Mark D. Plumbley:
Predictive Information in Gaussian Processes with Application to Music Analysis. GSI 2013: 650-657 - [c82]Ken O'Hanlon, Mark D. Plumbley:
Automatic Music Transcription using row weighted decompositions. ICASSP 2013: 16-20 - [c81]Dan Stowell, Saso Musevic, Jordi Bonada, Mark D. Plumbley:
Improved multiple birdsong tracking with distribution derivative method and Markov renewal process clustering. ICASSP 2013: 468-472 - [c80]Joachim Fritsch, Mark D. Plumbley:
Score informed audio source separation using constrained nonnegative matrix factorization and score synthesis. ICASSP 2013: 888-891 - [c79]Boris Mailhé, Bob L. Sturm, Mark D. Plumbley:
Behavior of greedy sparse representation algorithms on nested supports. ICASSP 2013: 5710-5714 - [c78]Dimitrios Giannoulis, Anssi Klapuri, Mark D. Plumbley:
Recognition of harmonic sounds in polyphonic audio using a missing feature approach. ICASSP 2013: 8658-8662 - [c77]Daniele Barchiesi, Mark D. Plumbley:
Learning incoherent subspaces for classification via supervised iterative projections and rotations. MLSP 2013: 1-6 - [c76]Nicolas Keriven, Ken O'Hanlon, Mark D. Plumbley:
Structured sparsity using backwards elimination for Automatic Music Transcription. MLSP 2013: 1-6 - [c75]Roland Badeau, Mark D. Plumbley:
Multichannel HR-NMF for modelling convolutive mixtures of non-stationary signals in the time-frequency domain. WASPAA 2013: 1-4 - [c74]Dimitrios Giannoulis, Emmanouil Benetos, Dan Stowell, Mathias Rossignol, Mathieu Lagrange, Mark D. Plumbley:
Detection and classification of acoustic scenes and events: An IEEE AASP challenge. WASPAA 2013: 1-4 - [i8]Dan Stowell, Saso Musevic, Jordi Bonada, Mark D. Plumbley:
Improved multiple birdsong tracking with distribution derivative method and Markov renewal process clustering. CoRR abs/1302.3462 (2013) - [i7]Dan Stowell, Mark D. Plumbley:
An open dataset for research on audio field recording archives: freefield1010. CoRR abs/1309.5275 (2013) - [i6]Dan Stowell, Mark D. Plumbley:
Large-scale analysis of frequency modulation in birdsong databases. CoRR abs/1311.4764 (2013) - 2012
- [j30]Adam M. Stark, Mark D. Plumbley:
Performance Following: Real-Time Prediction of Musical Sequences Without a Score. IEEE Trans. Speech Audio Process. 20(1): 190-199 (2012) - [j29]Norberto Degara, Enrique Argones-Rúa, Antonio S. Pena, Soledad Torres-Guijarro, Matthew E. P. Davies, Mark D. Plumbley:
Reliability-Informed Beat Tracking of Musical Signals. IEEE Trans. Speech Audio Process. 20(1): 290-301 (2012) - [j28]Amir Adler, Valentin Emiya, Maria G. Jafari, Michael Elad, Rémi Gribonval, Mark D. Plumbley:
Audio Inpainting. IEEE Trans. Speech Audio Process. 20(3): 922-932 (2012) - [c73]Henrik Ekeus, Samer A. Abdallah, Mark D. Plumbley, Peter W. McOwan:
The Melody Triangle: Exploring Pattern and Predictability in Music. MUME@AIIDE 2012 - [c72]Ken O'Hanlon, Hidehisa Nagano, Mark D. Plumbley:
Using Oracle Analysis for Decomposition-Based Automatic Music Transcription. CMMR 2012: 353-365 - [c71]Samer A. Abdallah, Henrik Ekeus, Peter Foster, Andrew Robertson, Mark D. Plumbley:
Cognitive music modelling: An information dynamics approach. CIP 2012: 1-8 - [c70]Fábio de Lima Hedayioglu, Maria G. Jafari, Sandra da Silva Mattos, Mark D. Plumbley, Miguel T. Coimbra:
Denoising and segmentation of the second heart sound using matching pursuit. EMBC 2012: 3440-3443 - [c69]Nicolae Cleju, Maria G. Jafari, Mark D. Plumbley:
Choosing analysis or synthesis recovery for sparse reconstruction. EUSIPCO 2012: 869-873 - [c68]Aris Gretsistas, Mark D. Plumbley:
An alternating descent algorithm for the off-grid DOA estimation problem with sparsity constraints. EUSIPCO 2012: 874-878 - [c67]Dan Stowell, Mark D. Plumbley:
Framewise heterodyne chirp analysis of birdsong. EUSIPCO 2012: 2694-2698 - [c66]Boris Mailhé, Mark D. Plumbley:
Dictionary Learning with Large Step Gradient Descent for Sparse Representations. LVA/ICA 2012: 231-238 - [c65]Aris Gretsistas, Mark D. Plumbley:
Group Polytope Faces Pursuit for Recovery of Block-Sparse Signals. LVA/ICA 2012: 255-262 - [c64]Hiromasa Fujihara, Anssi Klapuri, Mark D. Plumbley:
Instrumentation-based music similarity using sparse representations. ICASSP 2012: 433-436 - [c63]Ken O'Hanlon, Hidehisa Nagano, Mark D. Plumbley:
Structured sparsity for automatic music transcription. ICASSP 2012: 441-444 - [c62]Chris Cannam, Luís Figueira, Mark D. Plumbley:
Sound Software: Towards software reuse in audio and music research. ICASSP 2012: 2745-2748 - [c61]Boris Mailhé, Daniele Barchiesi, Mark D. Plumbley:
INK-SVD: Learning incoherent dictionaries for sparse representations. ICASSP 2012: 3573-3576 - [c60]Nicolae Cleju, Maria G. Jafari, Mark D. Plumbley:
Analysis-based sparse reconstruction with synthesis-based solvers. ICASSP 2012: 5401-5404 - [i5]Nicolae Cleju, Maria G. Jafari, Mark D. Plumbley:
Analysis-based sparse reconstruction with synthesis-based solvers. CoRR abs/1204.5347 (2012) - [i4]Dhavide A. Aruliah, C. Titus Brown, Neil P. Chue Hong, Matt Davis, Richard T. Guy, Steven H. D. Haddock, Katy Huff, Ian Mitchell, Mark D. Plumbley, Ben Waugh, Ethan P. White, Greg Wilson, Paul Wilson:
Best Practices for Scientific Computing. CoRR abs/1210.0530 (2012) - [i3]Dan Stowell, Mark D. Plumbley:
Segregating event streams and noise with a Markov renewal process model. CoRR abs/1211.2972 (2012) - 2011
- [j27]Maria G. Jafari, Mark D. Plumbley:
Fast Dictionary Learning for Sparse Representations of Speech Signals. IEEE J. Sel. Top. Signal Process. 5(5): 1025-1031 (2011) - [j26]Norberto Degara, Matthew E. P. Davies, Antonio S. Pena, Mark D. Plumbley:
Onset Event Decoding Exploiting the Rhythmic Structure of Polyphonic Music. IEEE J. Sel. Top. Signal Process. 5(6): 1228-1239 (2011) - [j25]Matthew E. P. Davies, Norberto Degara, Mark D. Plumbley:
Measuring the Performance of Beat Tracking Algorithms Using a Beat Error Histogram. IEEE Signal Process. Lett. 18(3): 157-160 (2011) - [c59]Boaz Ophir, Michael Elad, Nancy Bertin, Mark D. Plumbley:
Sequential minimal eigenvalues - an approach to analysis dictionary learning. EUSIPCO 2011: 1465-1469 - [c58]Ken O'Hanlon, Mark D. Plumbley:
Structure-aware dictionary learning with harmonic atoms. EUSIPCO 2011: 1761-1765 - [c57]Amir Adler, Valentin Emiya, Maria G. Jafari, Michael Elad, Rémi Gribonval, Mark D. Plumbley:
A constrained matching pursuit approach to audio declipping. ICASSP 2011: 329-332 - [c56]Fábio de Lima Hedayioglu, Maria G. Jafari, Sandra da Silva Mattos, Mark D. Plumbley, Miguel T. Coimbra:
Separating sources from sequentially acquired mixtures of heart signals. ICASSP 2011: 653-656 - [c55]Daniele Barchiesi, Mark D. Plumbley:
Dictionary learning of convolved signals. ICASSP 2011: 5812-5815 - [c54]Andrew Robertson, Adam M. Stark, Mark D. Plumbley:
Real-time Visual Beat Tracking using a Comb Filter Matrix. ICMC 2011 - [c53]Maria G. Jafari, Fábio de Lima Hedayioglu, Miguel T. Coimbra, Mark D. Plumbley:
Blind source separation of periodic sources from sequentially recorded instantaneous mixtures. ISPA 2011: 540-545 - [c52]Peter Foster, Anssi Klapuri, Mark D. Plumbley:
Causal Prediction of Continuous-Valued Music Features. ISMIR 2011: 501-506 - [c51]Tim Murray Browne, Di Mainstone, Nick Bryan-Kinns, Mark D. Plumbley:
The Medium is the Message: Composing Instruments and Performing Mappings. NIME 2011: 56-59 - [c50]Dimitrios Giannoulis, Daniele Barchiesi, Anssi Klapuri, Mark D. Plumbley:
On the disjointess of sources in music using different time-frequency representations. WASPAA 2011: 261-264 - 2010
- [j24]Mark D. Plumbley, Thomas Blumensath, Laurent Daudet, Rémi Gribonval, Mike E. Davies:
Sparse Representations in Audio and Music: From Coding to Source Separation. Proc. IEEE 98(6): 995-1005 (2010) - [c49]Ivan Damnjanovic, Matthew E. P. Davies, Mark D. Plumbley:
SMALLbox - An Evaluation Framework for Sparse Representations and Dictionary Learning Algorithms. LVA/ICA 2010: 418-425 - [c48]Aris Gretsistas, Mark D. Plumbley:
A Multichannel Spatial Compressed Sensing Approach for Direction of Arrival Estimation. LVA/ICA 2010: 458-465 - [c47]Aris Gretsistas, Ivan Damnjanovic, Mark D. Plumbley:
Gradient Polytope Faces Pursuit for large scale sparse recovery problems. ICASSP 2010: 2030-2033 - [c46]Adam M. Stark, Mark D. Plumbley:
Performance following: Tracking a performance without a score. ICASSP 2010: 2482-2485 - [c45]Florent Jaillet, Rémi Gribonval, Mark D. Plumbley, Hadi Zayyani:
An L1 criterion for dictionary learning by subspace identification. ICASSP 2010: 5482-5485 - [c44]Norberto Degara, Antonio S. Pena, Matthew E. P. Davies, Mark D. Plumbley:
Note onset detection using rhythmic structure. ICASSP 2010: 5526-5529 - [c43]Dan Stowell, Mark D. Plumbley:
Cross-associating unlabelled timbre distributions to create expressive musical mappings. WAPA 2010: 28-35 - [i2]Samer A. Abdallah, Mark D. Plumbley:
A measure of statistical complexity based on predictive information. CoRR abs/1012.1890 (2010)
2000 – 2009
- 2009
- [j23]Samer M. Abdallah, Mark D. Plumbley:
Information dynamics: patterns of expectation and surprise in the perception of music. Connect. Sci. 21(2&3): 89-117 (2009) - [j22]Dan Stowell, Andrew Robertson, Nick Bryan-Kinns, Mark D. Plumbley:
Evaluation of live human-computer music-making: Quantitative and qualitative approaches. Int. J. Hum. Comput. Stud. 67(11): 960-975 (2009) - [j21]Dan Stowell, Mark D. Plumbley:
Fast Multidimensional Entropy Estimation by k -d Partitioning. IEEE Signal Process. Lett. 16(6): 537-540 (2009) - [c42]Maria G. Jafari, Mark D. Plumbley:
Speech denoising based on a greedy adaptive dictionary algorithm. EUSIPCO 2009: 1423-1426 - [c41]Andrew Nesbit, Emmanuel Vincent, Mark D. Plumbley:
Benchmarking flexible adaptive time-frequency transforms for underdetermined audio source separation. ICASSP 2009: 37-40 - [c40]Keisuke Toyama, Mark D. Plumbley:
Using phase linearity in frequency-domain ICA to tackle the permutation problem. ICASSP 2009: 3165-3168 - [c39]Mark D. Plumbley, Marco Bevilacqua:
Sparse reconstruction for compressed sensing using Stagewise Polytope Faces Pursuit. DPS 2009: 1-8 - [c38]Andrew Robertson, Mark D. Plumbley:
Post-Processing Fiddle~: A Real-Time Multi-Pitch Tracking Technique Using Harmonic Partial Subtraction for Use within Live Performance Systems. ICMC 2009 - [c37]Adam M. Stark, Mark D. Plumbley:
Real-Time Chord Recognition for Live Performance. ICMC 2009 - [c36]Keisuke Toyama, Mark D. Plumbley:
Estimating Phase Linearity in the Frequency-Domain ICA Demixing Matrix. ICA 2009: 362-370 - [c35]Andrew Nesbit, Emmanuel Vincent, Mark D. Plumbley:
Extension of Sparse, Adaptive Signal Decompositions to Semi-blind Audio Source Separation. ICA 2009: 605-612 - [c34]Matthew E. P. Davies, Mark D. Plumbley, Douglas Eck:
Towards a musical beat emphasis function. WASPAA 2009: 61-64 - 2008
- [j20]Hans Laurberg, Mads Græsbøll Christensen, Mark D. Plumbley, Lars Kai Hansen, Søren Holdt Jensen:
Theorems on Positive Data: On the Uniqueness of NMF. Comput. Intell. Neurosci. 2008 (2008) - [j19]Maria G. Jafari, Emmanuel Vincent, Samer A. Abdallah, Mark D. Plumbley, Mike E. Davies:
An adaptive stereo basis method for convolutive blind audio source separation. Neurocomputing 71(10-12): 2087-2097 (2008) - [j18]Emmanuel Vincent, Mark D. Plumbley:
Efficient Bayesian inference for harmonic models via adaptive posterior factorization. Neurocomputing 72(1-3): 79-87 (2008) - [c33]Matthew E. P. Davies, Mark D. Plumbley:
Exploring the effect of rhythmic style classification on automatic tempo estimation. EUSIPCO 2008: 1-5 - [c32]Maria G. Jafari, Mark D. Plumbley:
Separation of stereo speech signals based on a sparse dictionary algorithm. EUSIPCO 2008: 1-5 - [c31]Yasunori Nishimori, Shotaro Akaho, Mark D. Plumbley:
Natural Conjugate Gradient on Complex Flag Manifolds for Complex Independent Subspace Analysis. ICANN (1) 2008: 165-174 - [c30]Andrew Nesbit, Mark D. Plumbley:
Oracle estimation of adaptive cosine packet transforms for underdetermined audio source separation. ICASSP 2008: 41-44 - [c29]Adam M. Stark, Matthew E. P. Davies, Mark D. Plumbley:
Rhythmic Analysis for Real-Time audio effects. ICMC 2008 - [c28]Dan Stowell, Mark D. Plumbley, Nick Bryan-Kinns:
Discourse Analysis Evaluation Method for Expressive Musical Interfaces. NIME 2008: 81-86 - [c27]Jean-Baptiste Thiebaut, Samer A. Abdallah, Andrew Robertson, Nick Bryan-Kinns, Mark D. Plumbley:
Real Time Gesture Learning and Recognition: Towards Automatic Categorization. NIME 2008: 215-218 - [c26]Andrew Robertson, Mark D. Plumbley, Nick Bryan-Kinns:
A Turing Test for B-Keeper: Evaluating an Interactive. NIME 2008: 319-324 - 2007
- [j17]Andrew Nesbit, Mark D. Plumbley, Mike E. Davies:
Audio source separation with a signal-adaptive local cosine transform. Signal Process. 87(8): 1848-1858 (2007) - [j16]Emmanuel Vincent, Rémi Gribonval, Mark D. Plumbley:
Oracle estimators for the benchmarking of source separation algorithms. Signal Process. 87(8): 1933-1950 (2007) - [j15]Matthew E. P. Davies, Mark D. Plumbley:
Context-Dependent Beat Tracking of Musical Audio. IEEE Trans. Speech Audio Process. 15(3): 1009-1020 (2007) - [j14]Emmanuel Vincent, Mark D. Plumbley:
Low Bit-Rate Object Coding of Musical Audio Using Bayesian Harmonic Models. IEEE Trans. Speech Audio Process. 15(4): 1273-1282 (2007) - [j13]Mark D. Plumbley:
On Polar Polytopes and the Recovery of Sparse Representations. IEEE Trans. Inf. Theory 53(9): 3188-3195 (2007) - [c25]Mark D. Plumbley:
Dictionary Learning for L1-Exact Sparse Coding. ICA 2007: 406-413 - [c24]Maria G. Jafari, Mark D. Plumbley:
The Role of High Frequencies in Convolutive Blind Source Separation of Speech Signals. ICA 2007: 488-494 - [c23]Matthew E. P. Davies, Mark D. Plumbley:
On the Use of Entropy for Beat Tracking Evaluation. ICASSP (4) 2007: 1305-1308 - [c22]Mark D. Plumbley:
Geometry and Manifolds for Independent Component Analysis. ICASSP (4) 2007: 1397-1400 - [c21]Yasunori Nishimori, Shotaro Akaho, Samer A. Abdallah, Mark D. Plumbley:
Flag Manifolds for Subspace ICA Problems. ICASSP (4) 2007: 1417-1420 - [c20]Dan Stowell, Mark D. Plumbley:
Adaptive whitening for Improved Real-Time audio onset Detection. ICMC 2007 - [c19]Andrew Robertson, Mark D. Plumbley:
B-Keeper: A Beat-Tracker for Live Performance. NIME 2007: 234-237 - [c18]Adam M. Stark, Mark D. Plumbley, Matthew E. P. Davies:
Real-Time Beat-Synchronous Audio Effects. NIME 2007: 344-345 - [p2]Mike E. Davies, Maria G. Jafari, Samer A. Abdallah, Emmanuel Vincent, Mark D. Plumbley:
Blind Source Separation using Space-Time Independent Component Analysis. Blind Speech Separation 2007: 79-99 - [e1]Mike E. Davies, Christopher J. James, Samer A. Abdallah, Mark D. Plumbley:
Independent Component Analysis and Signal Separation, 7th International Conference, ICA 2007, London, UK, September 9-12, 2007. Lecture Notes in Computer Science 4666, Springer 2007, ISBN 978-3-540-74493-1 [contents] - 2006
- [j12]Mark D. Plumbley, Samer A. Abdallah, Thomas Blumensath, Michael E. Davies:
Sparse representations of polyphonic music. Signal Process. 86(3): 417-431 (2006) - [j11]Samer A. Abdallah, Mark D. Plumbley:
Unsupervised analysis of polyphonic music by sparse coding. IEEE Trans. Neural Networks 17(1): 179-196 (2006) - [c17]Matthew E. P. Davies, Mark D. Plumbley:
A spectral difference approach to downbeat extraction in musical audio. EUSIPCO 2006: 1-4 - [c16]Andrew Nesbit, Mike E. Davies, Mark D. Plumbley, Mark B. Sandler:
Source extraction from two-channel mixtures by joint cosine packet analysis. EUSIPCO 2006: 1-5 - [c15]Maria G. Jafari, Samer A. Abdallah, Mark D. Plumbley, Mike E. Davies:
Sparse Coding for Convolutive Blind Audio Source Separation. ICA 2006: 132-139 - [c14]Mark D. Plumbley:
Recovery of Sparse Representations by Polytope Faces Pursuit. ICA 2006: 206-213 - [c13]Yasunori Nishimori, Shotaro Akaho, Mark D. Plumbley:
Riemannian Optimization Method on the Flag Manifold for Independent Subspace Analysis. ICA 2006: 295-302 - [c12]Emmanuel Vincent, Mark D. Plumbley:
Single-Channel Mixture Decomposition Using Bayesian Harmonic Models. ICA 2006: 722-730 - 2005
- [j10]Mark D. Plumbley:
Geometrical methods for non-negative ICA: Manifolds, Lie groups and toral subalgebras. Neurocomputing 67: 161-197 (2005) - [c11]Matthew E. P. Davies, Mark D. Plumbley:
Beat tracking with a two state model [music applications]. ICASSP (3) 2005: 241-244 - [i1]Mark D. Plumbley:
Polar Polytopes and Recovery of Sparse Representations. CoRR abs/cs/0510032 (2005) - 2004
- [j9]Erkki Oja, Mark D. Plumbley:
Blind Separation of Positive Sources by Globally Convergent Gradient Search. Neural Comput. 16(9): 1811-1825 (2004) - [j8]Mark D. Plumbley, Erkki Oja:
A "nonnegative PCA" algorithm for independent component analysis. IEEE Trans. Neural Networks 15(1): 66-76 (2004) - [c10]Mark D. Plumbley:
Optimization Using Fourier Expansion over a Geodesic for Non-negative ICA. ICA 2004: 49-56 - [c9]Samer A. Abdallah, Mark D. Plumbley:
Application of Geometric Dependency Analysis to the Separation of Convolved Mixtures. ICA 2004: 540-547 - [c8]Mark D. Plumbley:
Lie Group Methods for Optimization with Orthogonality Constraints. ICA 2004: 1245-1252 - [c7]Paul Brossier, Juan Pablo Bello, Mark D. Plumbley:
Real-time temporal segmentation of note objects in music signals. ICMC 2004 - [c6]Samer M. Abdallah, Mark D. Plumbley:
Polyphonic transcription by non-negative sparse coding of power spectra. ISMIR 2004 - [c5]Paul Brossier, Juan Pablo Bello, Mark D. Plumbley:
Fast labelling of notes in music signals. ISMIR 2004 - [c4]Matthew E. P. Davies, Mark D. Plumbley:
Causal Tempo Tracking of Audio. ISMIR 2004 - 2003
- [j7]Mark D. Plumbley:
Algorithms for nonnegative independent component analysis. IEEE Trans. Neural Networks 14(3): 534-543 (2003) - 2002
- [j6]Mark D. Plumbley, Samer A. Abdallah, Juan Pablo Bello, Mike E. Davies, Giuliano Monti, Mark B. Sandler:
Automatic Music Transcription and Audio Source Separation. Cybern. Syst. 33(6): 603-627 (2002) - [j5]Mark D. Plumbley:
Conditions for nonnegative independent component analysis. IEEE Signal Process. Lett. 9(6): 177-180 (2002) - 2000
- [c3]Ian Johnson, Mark D. Plumbley:
On-Line Connectionist Q-Learning Produces Unreliable Performance with A Synonym Finding Task. IJCNN (3) 2000: 451-458 - [p1]Mark D. Plumbley:
Information Density and Cortical Magnification Factors. Information Theory and the Brain 2000: 305-317
1990 – 1999
- 1997
- [c2]Mark D. Plumbley:
Communications and neural networks: theory and practice. ICASSP 1997: 135-138 - 1996
- [j4]Suzanna Becker, Mark D. Plumbley:
Unsupervised Neural Network Learning Procedures for Feature Extraction and Classification. Appl. Intell. 6(3): 185-203 (1996) - 1995
- [j3]Mark D. Plumbley:
Lyapunov functions for convergence of principal component algorithms. Neural Networks 8(1): 11-23 (1995) - 1993
- [j2]G. E. Robbins, Mark D. Plumbley, John C. Hughes, Frank Fallside, Richard W. Prager:
Generation and Adaptation of Neural Networks by Evolutionary Techniques (GANNET). Neural Comput. Appl. 1(1): 23-31 (1993) - [j1]Mark D. Plumbley:
Efficient information transfer and anti-Hebbian neural networks. Neural Networks 6(6): 823-833 (1993) - 1991
- [c1]Mark D. Plumbley, Frank Fallside:
The effect of receptor signal-to-noise levels on optimal filtering in a sensory system. ICASSP 1991: 2321-2324
Coauthor Index
[c190] [c188] [i93] [i90] [i83] [i82] [i81] [i77] [c184] [c183] [c177] [c176] [i74] [i73] [i68] [i67] [i64] [i63] [i62] [i60] [i58] [j57] [j56] [c166] [c164] [i55] [j55] [j54] [c161] [c159] [c157] [c156] [i46] [i45] [i44] [i43] [i41] [j52] [j51] [c155] [c153] [c150] [c149] [c148] [c146] [i40] [i39] [i38] [i37] [i36] [i35] [i32] [i31] [c144] [c143] [c142] [c137] [c135] [c134] [c133] [i29] [i28] [c126] [c125] [c119] [c115] [c113] [i26] [i25] [i23] [i22] [i20] [i19] [c110] [i13]
[c190] [c189] [c188] [c186] [i95] [i94] [i93] [i89] [i88] [i86] [i84] [i83] [i82] [i81] [i80] [i79] [i78] [j61] [c183] [c181] [c180] [c179] [c178] [c176] [c174] [c173] [i76] [i75] [i73] [i72] [i70] [i69] [i68] [i67] [i65] [i63] [i62] [i61] [i60] [i58] [i57] [i56] [j59] [c170] [c169] [c168] [c167] [c166] [c164] [c163] [c162] [i55] [i53] [i52] [i51] [i49] [i48] [i47] [j55] [j54] [c161] [c160] [c157] [c156] [i46] [i45] [i44] [i43] [j52] [j51] [j50] [c155] [c148] [c147] [c146] [i40] [i39] [i37] [i36] [i32] [i31] [c145] [c143] [c142] [c137] [c136] [c135] [c134] [c133] [c131] [i29] [i28] [j46] [c123] [c119] [c118] [c117] [c116] [c115] [c113] [c111] [i26] [i25] [i23] [i22] [i20] [i19] [j41] [c110] [c108] [c107] [i18] [i17] [i16] [i13]
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