Shaojin Ding

1.1k total citations · 1 hit paper
22 papers, 593 citations indexed

About

Shaojin Ding is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shaojin Ding has authored 22 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 15 papers in Signal Processing and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shaojin Ding's work include Speech Recognition and Synthesis (21 papers), Speech and Audio Processing (15 papers) and Music and Audio Processing (9 papers). Shaojin Ding is often cited by papers focused on Speech Recognition and Synthesis (21 papers), Speech and Audio Processing (15 papers) and Music and Audio Processing (9 papers). Shaojin Ding collaborates with scholars based in United States, China and United Kingdom. Shaojin Ding's co-authors include Tianlong Chen, Wuyang Chen, Jingyi Xie, Zhou Ren, Ye Yuan, Yang Yang, Ricardo Gutiérrez‐Osuna, Guanlong Zhao, Xinyu Gong and Ian McGraw and has published in prestigious journals such as Speech Communication, IEEE/ACM Transactions on Audio Speech and Language Processing and Computer Speech & Language.

In The Last Decade

Shaojin Ding

22 papers receiving 572 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.

ABD-Net: Attentive but Diverse Person Re-Identification

2019 360 citations Tianlong Chen, Shaojin Ding et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shaojin Ding United States	10	374	218	146	145	36	22	593
Albert Clapés Spain	9	228 0.6×	65 0.3×	60 0.4×	17 0.1×	13 0.4×	19	334
Elhocine Boutellaa Algeria	12	270 0.7×	29 0.1×	71 0.5×	110 0.8×	15 0.4×	34	336
Yufei Zha China	11	273 0.7×	64 0.3×	17 0.1×	22 0.2×	22 0.6×	51	373
Martin Bäuml Germany	12	446 1.2×	86 0.4×	43 0.3×	72 0.5×	6 0.2×	18	484
Constantin Vertan Romania	12	271 0.7×	38 0.2×	24 0.2×	43 0.3×	25 0.7×	78	411
Thomas S. Huang United States	8	663 1.8×	85 0.4×	45 0.3×	193 1.3×	22 0.6×	13	715
Matthias Eichner Germany	9	138 0.4×	129 0.6×	38 0.3×	59 0.4×	26 0.7×	25	298
David Gerhard Canada	9	134 0.4×	62 0.3×	36 0.2×	187 1.3×	25 0.7×	39	311
V. Ramu Reddy India	10	41 0.1×	138 0.6×	49 0.3×	136 0.9×	65 1.8×	22	277

Countries citing papers authored by Shaojin Ding

Since Specialization

Citations

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

Fields of papers citing papers by Shaojin Ding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaojin Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Shaojin Ding. A scholar is included among the top collaborators of Shaojin Ding 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 Shaojin Ding. Shaojin Ding 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:

20 of 20 papers shown

1.

Ding, Shaojin, Yanzhang He, Bo Li, et al.. (2024). USM-Lite: Quantization and Sparsity Aware Fine-Tuning for Speech Recognition with Universal Speech Models. 10756–10760. 1 indexed citations

2.

Hernandez, Steven M., Ding Zhao, Shaojin Ding, et al.. (2023). Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Models. 1–5. 4 indexed citations

3.

Ding, Shaojin, et al.. (2023). 2-bit Conformer quantization for automatic speech recognition. 4908–4912. 5 indexed citations

4.

Ding, Shaojin, Arun Narayanan, Quan Wang, et al.. (2023). Conditional Conformer: Improving Speaker Modulation For Single And Multi-User Speech Enhancement. 1–5. 1 indexed citations

5.

Cai, Xingyu, et al.. (2023). Efficient Cascaded Streaming ASR System Via Frame Rate Reduction. 1–8. 2 indexed citations

6.

Ding, Shaojin, et al.. (2022). Personal VAD 2.0: Optimizing Personal Voice Activity Detection for On-Device Speech Recognition. Interspeech 2022. 3744–3748. 19 indexed citations

7.

Ding, Shaojin, et al.. (2022). 4-bit Conformer with Native Quantization Aware Training for Speech Recognition. Interspeech 2022. 1711–1715. 16 indexed citations

8.

Ding, Shaojin, et al.. (2022). Towards Lifelong Learning of Multilingual Text-to-Speech Synthesis. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 30. 8022–8026. 1 indexed citations

9.

Ding, Shaojin, Weiran Wang, Ding Zhao, et al.. (2022). A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes. Interspeech 2022. 6 indexed citations

10.

Ding, Shaojin, Jia Ye, Ke Hu, & Quan Wang. (2021). Textual Echo Cancellation. 40. 548–555. 5 indexed citations

11.

Zhao, Guanlong, Shaojin Ding, & Ricardo Gutiérrez‐Osuna. (2021). Converting Foreign Accent Speech Without a Reference. IEEE/ACM Transactions on Audio Speech and Language Processing. 29. 2367–2381. 10 indexed citations

12.

Ding, Shaojin, Guanlong Zhao, & Ricardo Gutiérrez‐Osuna. (2021). Accentron: Foreign accent conversion to arbitrary non-native speakers using zero-shot learning. Computer Speech & Language. 72. 101302–101302. 14 indexed citations

13.

Ding, Shaojin, et al.. (2020). AutoSpeech: Neural Architecture Search for Speaker Recognition. 916–920. 35 indexed citations

14.

Ding, Shaojin, Guanlong Zhao, & Ricardo Gutiérrez‐Osuna. (2020). Improving the Speaker Identity of Non-Parallel Many-to-Many Voice Conversion with Adversarial Speaker Recognition. 776–780. 12 indexed citations

15.

Zhao, Guanlong, Shaojin Ding, & Ricardo Gutiérrez‐Osuna. (2019). Foreign Accent Conversion by Synthesizing Speech from Phonetic Posteriorgrams. 2843–2847. 29 indexed citations

16.

Ding, Shaojin, Sinem Sonsaat, Guanlong Zhao, et al.. (2019). Golden speaker builder – An interactive tool for pronunciation training. Speech Communication. 115. 51–66. 33 indexed citations

17.

Chen, Tianlong, Shaojin Ding, Jingyi Xie, et al.. (2019). ABD-Net: Attentive but Diverse Person Re-Identification. 8350–8360. 360 indexed citations breakdown →

18.

Ding, Shaojin, et al.. (2019). Learning Structured Sparse Representations for Voice Conversion. IEEE/ACM Transactions on Audio Speech and Language Processing. 28. 343–354. 7 indexed citations

19.

Ding, Shaojin, et al.. (2018). Learning Structured Dictionaries for Exemplar-based Voice Conversion. 481–485. 3 indexed citations

20.

Ding, Shaojin, et al.. (2018). Improving Sparse Representations in Exemplar-Based Voice Conversion with a Phoneme-Selective Objective Function. 476–480. 1 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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