Yichong Leng

643 total citations · 1 hit paper
10 papers, 152 citations indexed

About

Yichong Leng is a scholar working on Artificial Intelligence, Signal Processing and Infectious Diseases. According to data from OpenAlex, Yichong Leng has authored 10 papers receiving a total of 152 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Signal Processing and 0 papers in Infectious Diseases. Recurrent topics in Yichong Leng's work include Speech Recognition and Synthesis (8 papers), Natural Language Processing Techniques (5 papers) and Topic Modeling (3 papers). Yichong Leng is often cited by papers focused on Speech Recognition and Synthesis (8 papers), Natural Language Processing Techniques (5 papers) and Topic Modeling (3 papers). Yichong Leng collaborates with scholars based in China, United States and Hong Kong. Yichong Leng's co-authors include Xu Tan, Sheng Zhao, Tao Qin, Frank K. Soong, Xiang‐Yang Li, Zhifang Guo, Tie‐Yan Liu, Yihan Wu, Jian Cong and Lei He and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neural Information Processing Systems and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Yichong Leng

10 papers receiving 148 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality

2024 49 citations Xu Tan, Jiawei Chen et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers

Yichong Leng

AI

SP

CVPR

ECP

CSE

Paden Tomasello France

Stanislav Beliaev United States

Samuel Kriman United States

Jocelyn Huang United States

Tatiana Likhomanenko United States

Julián Salazar United States

Julian Chan United States

Ziyang Ma China

Huyen Nguyen United States

Puming Zhan United States

Paden Tomasello France

Yichong Leng

140 ×1.2

AI

49 ×0.7

SP

22 ×0.8

CVPR

11 ×1.2

ECP

2 ×0.4

CSE

Citations per year, relative to Yichong Leng Yichong Leng (= 1×) peers Paden Tomasello

Countries citing papers authored by Yichong Leng

Since Specialization

Citations

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

Fields of papers citing papers by Yichong Leng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yichong Leng

This figure shows the co-authorship network connecting the top 25 collaborators of Yichong Leng. A scholar is included among the top collaborators of Yichong Leng 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 Yichong Leng. Yichong Leng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Tan, Xu, Jiawei Chen, Haohe Liu, et al.. (2024). NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(6). 4234–4245. 49 indexed citations breakdown →

2.

Liu, Wenrui, Yunfei Chu, Ziyue Karen Jiang, et al.. (2024). AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension. 1979–1998. 4 indexed citations

3.

Dong, Hande, et al.. (2024). Improving Code Search with Hard Negative Sampling Based on Fine-tuning. 221–230. 1 indexed citations

4.

Guo, Zhifang, Yichong Leng, Yihan Wu, Sheng Zhao, & Xu Tan. (2023). Prompttts: Controllable Text-To-Speech With Text Descriptions. 1–5. 26 indexed citations

5.

Leng, Yichong, et al.. (2023). SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition. Proceedings of the AAAI Conference on Artificial Intelligence. 37(11). 13034–13042. 6 indexed citations

6.

Shen, Kai, Yichong Leng, Xu Tan, et al.. (2022). Mask the Correct Tokens: An Embarrassingly Simple Approach for Error Correction. 10367–10380. 3 indexed citations

7.

Zhang, Guangyan, Yichong Leng, Ying Qin, et al.. (2022). A Study on the Efficacy of Model Pre-Training In Developing Neural Text-to-Speech System. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 32. 6087–6091. 1 indexed citations

8.

Chen, Jiawei, Xu Tan, Yichong Leng, et al.. (2021). Speech-T: Transducer for Text to Speech and Beyond. Neural Information Processing Systems. 34. 4 indexed citations

9.

Leng, Yichong, Xu Tan, Sheng Zhao, et al.. (2021). MBNET: MOS Prediction for Synthesized Speech with Mean-Bias Network. 391–395. 49 indexed citations

10.

Xia, Yingce, Xu Tan, Fei Tian, et al.. (2019). Microsoft Research Asia’s Systems for WMT19. 424–433. 9 indexed citations

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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