Li Deng

53.7k citations

316 papers · 30.4k indexed · 19 hit papers · h-index 69

Impact in

Signal Processing top 0.01%
- Speech and Audio Processing
- Music and Audio Processing
Artificial Intelligence top 0.01%
- Speech Recognition and Synthesis
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning

Papers in ⓘ

Signal Processing 182
- Speech and Audio Processing 151
- Music and Audio Processing 95
Artificial Intelligence 282
- Speech Recognition and Synthesis 195
- Natural Language Processing Techniques 66
- Topic Modeling 61
- Speech and dialogue systems 36

Co-authors: Dong Yu (78 shared papers)Xiaodong He (57 shared papers)Abdelrahman Mohamed (7 shared papers)Geoffrey E. Hinton (5 shared papers)Brian Kingsbury (4 shared papers)George E. Dahl (6 shared papers)Andrew Senior (4 shared papers)Alex Acero (59 shared papers)
Journals: IEEE Signal Processing Magazine (19 papers)IEEE Transactions on Speech and Audio Processing (10 papers)Computer Speech & Language (8 papers)IEEE Transactions on Audio Speech and Language Processing (8 papers)Signal Processing (8 papers)
Partner nations: United States Canada United Kingdom

In The Last Decade

Li Deng

304 papers receiving 28.1k citations

Hit Papers

15 papers align trajectories log scale

Multimodal Intelligence: Representation Learning, Information Fusion, and Applications 2020 · 292 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2020 IEEE Journal of Selected Topics in Signal Processing
2016 Stacked Attention Networks for Image Question Answering
2015 From captions to visual concepts and back
2014 IEEE/ACM Transactions on Audio Speech and Language Processing
2014 APSIPA Transactions on Signal and Information Processing
2014 Learning semantic representations using convolutional neural networks for web search
2014 IEEE/ACM Transactions on Audio Speech and Language Processing
2014 A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval
2014 Deep Learning: Methods and Applications
2014 now publishers, Inc. eBooks
2013 Recent advances in deep learning for speech research at Microsoft
2013 Learning deep structured semantic models for web search using clickthrough data
2013 New types of deep neural network learning for speech recognition and related applications: an overview
2013 Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers
2013 Large-scale malware classification using random projections and neural networks
2012 IEEE Signal Processing Magazine
2012 IEEE Signal Processing Magazine
2010 Binary coding of speech spectrograms using a deep auto-encoder
2010 IEEE Signal Processing Magazine

Peers

Countries citing papers authored by Li Deng

Since Specialization

Citations

This map shows the geographic impact of Li Deng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Li Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Deng more than expected).

Fields of papers citing papers by Li Deng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li Deng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Li Deng. The network helps show where Li Deng may publish in the future.

Co-authors

The 25 scholars most cited alongside Li Deng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Li Deng Line = papers co-authored together Li Deng links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 316 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups IEEE Signal Processing Magazine ·Geoffrey E. Hinton, Li Deng, Dong Yu, George E. Dahl, Abdelrahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N. Sainath, Brian Kingsbury Hit paper breakdown →	2012	6614
2	Deep Learning: Methods and Applications Li Deng, Dong Yu Hit paper breakdown →	2014	2335
3	Convolutional Neural Networks for Speech Recognition IEEE/ACM Transactions on Audio Speech and Language Processing ·Ossama Abdel‐Hamid, Abdelrahman Mohamed, Hui Jiang, Li Deng, Gerald Penn, Dong Yu Hit paper breakdown →	2014	1566
4	Deep Learning: Methods and Applications now publishers, Inc. eBooks ·Li Deng Hit paper breakdown →	2014	1220
5	Stacked Attention Networks for Image Question Answering Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Smola Hit paper breakdown →	2016	1188
6	Deep Neural Networks for Acoustic Modeling in Speech Recognition IEEE Signal Processing Magazine ·Geoffrey E. Hinton, Li Deng, Dong Yu, George E. Dahl, Abdelrahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N. Sainath, Brian Kingsbury Hit paper breakdown →	2012	1169
7	Learning deep structured semantic models for web search using clickthrough data Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, Larry Heck Hit paper breakdown →	2013	1116
8	From captions to visual concepts and back Hao Fang, Saurabh Gupta, Forrest Iandola, Rupesh K. Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John Platt, C. Lawrence Zitnick, Geoffrey Zweig Hit paper breakdown →	2015	774
9	New types of deep neural network learning for speech recognition and related applications: an overview Li Deng, Geoffrey E. Hinton, Brian Kingsbury Hit paper breakdown →	2013	738
10	Recent advances in deep learning for speech research at Microsoft Li Deng, Jinyu Li, Jui-Ting Huang, Kaisheng Yao, Dong Yu, Frank Seide, Michael L. Seltzer, Geoff Zweig, Xiaodong He, J. D. Williams, Yifan Gong, Alex Acero Hit paper breakdown →	2013	510
11	A tutorial survey of architectures, algorithms, and applications for deep learning APSIPA Transactions on Signal and Information Processing ·Li Deng Hit paper breakdown →	2014	458
12	Learning semantic representations using convolutional neural networks for web search Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, Grégoire Mesnil Hit paper breakdown →	2014	419
13	A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, Grégoire Mesnil Hit paper breakdown →	2014	401
14	Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers Jui-Ting Huang, Jinyu Li, Dong Yu, Li Deng, Yifan Gong Hit paper breakdown →	2013	400
15	An Overview of Noise-Robust Automatic Speech Recognition IEEE/ACM Transactions on Audio Speech and Language Processing ·Jinyu Li, Li Deng, Yifan Gong, Reinhold Haeb‐Umbach Hit paper breakdown →	2014	373
16	Deep Learning and Its Applications to Signal and Information Processing [Exploratory DSP IEEE Signal Processing Magazine ·Dong Yu, Li Deng Hit paper breakdown →	2010	336
17	Multimodal Intelligence: Representation Learning, Information Fusion, and Applications IEEE Journal of Selected Topics in Signal Processing ·Chao Zhang, Zichao Yang, Xiaodong He, Li Deng Hit paper breakdown →	2020	292
18	Using Recurrent Neural Networks for Slot Filling in Spoken Language Understanding IEEE/ACM Transactions on Audio Speech and Language Processing ·Grégoire Mesnil, Yann Dauphin, Kaisheng Yao, Yoshua Bengio, Li Deng, Dilek Hakkani‐Tür, Xiaodong He, Larry Heck, Gökhan Tür, Dong Yu, Geoffrey Zweig	2014	271
19	Multi-Domain Joint Semantic Frame Parsing Using Bi-Directional RNN-LSTM Dilek Hakkani‐Tür, Gökhan Tür, Aslı Çelikyılmaz, Yun-Nung Chen, Jianfeng Gao, Li Deng, Ye‐Yi Wang	2016	270
20	Large-scale malware classification using random projections and neural networks George E. Dahl, Jack W. Stokes, Li Deng, Dong Yu Hit paper breakdown →	2013	270

About Li Deng

Li Deng is a scholar working on Signal Processing, Artificial Intelligence, Computational Mathematics, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 316 papers that have together received 30.4k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (195 papers), Speech and Audio Processing (151 papers), Music and Audio Processing (95 papers), Natural Language Processing Techniques (66 papers), Topic Modeling (61 papers), Speech and dialogue systems (36 papers), Phonetics and Phonology Research (30 papers) and Multimodal Machine Learning Applications (22 papers). The work is most often cited by research in Signal Processing (9.8k citations), Artificial Intelligence (19.3k citations), Computer Vision and Pattern Recognition (7.8k citations), Computational Mathematics (83 citations) and Experimental and Cognitive Psychology (1.2k citations). Li Deng has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Dong Yu, Xiaodong He, Abdelrahman Mohamed, Geoffrey E. Hinton, Brian Kingsbury, George E. Dahl, Andrew Senior, Alex Acero, Navdeep Jaitly and Tara N. Sainath. Their work appears in journals such as IEEE Signal Processing Magazine, IEEE Transactions on Speech and Audio Processing, Computer Speech & Language, IEEE Transactions on Audio Speech and Language Processing and Signal Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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