Zhanlei Yang

523 total citations
23 papers, 329 citations indexed

About

Zhanlei Yang is a scholar working on Artificial Intelligence, Signal Processing and Computational Mechanics. According to data from OpenAlex, Zhanlei Yang has authored 23 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 17 papers in Signal Processing and 4 papers in Computational Mechanics. Recurrent topics in Zhanlei Yang's work include Speech and Audio Processing (16 papers), Speech Recognition and Synthesis (16 papers) and Music and Audio Processing (12 papers). Zhanlei Yang is often cited by papers focused on Speech and Audio Processing (16 papers), Speech Recognition and Synthesis (16 papers) and Music and Audio Processing (12 papers). Zhanlei Yang collaborates with scholars based in China, United Kingdom and United States. Zhanlei Yang's co-authors include Wenju Liu, Hao Zheng, Shan Liang, Pengfei Hu, Mingming Chen, Jian Huang, Shuai Nie, Zheng Lian, Jianhua Tao and Bin Liu and has published in prestigious journals such as Pattern Recognition, Neural Networks and Speech Communication.

In The Last Decade

Zhanlei Yang

20 papers receiving 310 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhanlei Yang China 10 185 122 62 46 19 23 329
Simon Leglaive France 8 163 0.9× 185 1.5× 66 1.1× 32 0.7× 14 0.7× 20 352
Mengxiao Bi China 7 276 1.5× 255 2.1× 63 1.0× 13 0.3× 28 1.5× 13 397
Jinlin Liu China 8 74 0.4× 63 0.5× 88 1.4× 69 1.5× 9 0.5× 21 280
K.K. Paliwal Australia 9 209 1.1× 193 1.6× 46 0.7× 23 0.5× 18 0.9× 22 339
Jinhui Chen Japan 11 122 0.7× 71 0.6× 94 1.5× 63 1.4× 22 1.2× 44 294
Dongchao Yang China 9 133 0.7× 145 1.2× 108 1.7× 8 0.2× 15 0.8× 32 322
Pierre Lanchantin United Kingdom 14 434 2.3× 317 2.6× 98 1.6× 44 1.0× 5 0.3× 40 572
R. Coelho Brazil 10 111 0.6× 235 1.9× 64 1.0× 62 1.3× 46 2.4× 32 331

Countries citing papers authored by Zhanlei Yang

Since Specialization
Citations

This map shows the geographic impact of Zhanlei Yang'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 Zhanlei Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhanlei Yang more than expected).

Fields of papers citing papers by Zhanlei Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhanlei Yang. 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 Zhanlei Yang. The network helps show where Zhanlei Yang may publish in the future.

Co-authorship network of co-authors of Zhanlei Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhanlei Yang. A scholar is included among the top collaborators of Zhanlei Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhanlei Yang. Zhanlei Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Nie, Shuai, et al.. (2022). Masking-based Neural Beamformer for Multichannel Speech Enhancement. 125–129. 1 indexed citations
2.
Liang, Shan, et al.. (2021). Deep neural network-based generalized sidelobe canceller for dual-channel far-field speech recognition. Neural Networks. 141. 225–237. 20 indexed citations
3.
Liang, Shan, et al.. (2021). Exploiting the directional coherence function for multichannel source extraction. Speech Communication. 128. 1–14.
4.
Lian, Zheng, Jianhua Tao, Bin Liu, et al.. (2020). Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition. 394–398. 19 indexed citations
5.
Lian, Zheng, Jianhua Tao, Bin Liu, et al.. (2020). Conversational Emotion Recognition Using Self-Attention Mechanisms and Graph Neural Networks. 2347–2351. 22 indexed citations
6.
Liu, Bin, et al.. (2019). Loss and Double-edge-triggered Detector for Robust Small-footprint Keyword Spotting. 6361–6365. 11 indexed citations
7.
Nie, Shuai, et al.. (2018). Stochastic Multiple Choice Learning for Acoustic Modeling. 15. 1–6. 2 indexed citations
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Zheng, Hao, et al.. (2015). Improving deep neural networks using softplus units. 1–4. 134 indexed citations
11.
Chen, M., Zhanlei Yang, & Wenju Liu. (2014). Deep neural networks for Mandarin tone recognition. 1154–1158. 8 indexed citations
12.
Chen, M., et al.. (2014). Improving native accent identification using deep neural networks. 2170–2174. 2 indexed citations
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14.
Hao, Chao, Zhanlei Yang, & Wenju Liu. (2013). Improved tone modeling by exploiting articulatory features for Mandarin speech recognition. Journal of Computer Applications. 33(10). 2939–2944. 1 indexed citations
15.
Hu, Pengfei, et al.. (2013). Latent topic model for audio retrieval. Pattern Recognition. 47(3). 1138–1143. 31 indexed citations
16.
Hao, Chao, Zhanlei Yang, & Wenju Liu. (2012). Improved tone modeling by exploiting articulatory features for mandarin speech recognition. 4741–4744. 9 indexed citations
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Liu, Wenju, et al.. (2009). A novel interpolated N-gram language model based on class hierarchy. 18. 1–5. 2 indexed citations
20.

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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