Zhongxin Bai

520 total citations · 1 hit paper
10 papers, 320 citations indexed

About

Zhongxin Bai is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhongxin Bai has authored 10 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Signal Processing, 9 papers in Artificial Intelligence and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Zhongxin Bai's work include Speech Recognition and Synthesis (9 papers), Speech and Audio Processing (8 papers) and Music and Audio Processing (7 papers). Zhongxin Bai is often cited by papers focused on Speech Recognition and Synthesis (9 papers), Speech and Audio Processing (8 papers) and Music and Audio Processing (7 papers). Zhongxin Bai collaborates with scholars based in China. Zhongxin Bai's co-authors include Xiao-Lei Zhang, Jingdong Chen, Susanto Rahardja, Yingmin Wang and Feng Zhou and has published in prestigious journals such as Neural Networks, Speech Communication and IEEE Wireless Communications Letters.

In The Last Decade

Zhongxin Bai

10 papers receiving 304 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.

Speaker recognition based on deep learning: An overview

2021 224 citations Zhongxin Bai, Xiao-Lei Zhang Neural Networks profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhongxin Bai China	6	254	219	39	17	9	10	320
Xing Fan United States	11	323 1.3×	178 0.8×	76 1.9×	29 1.7×	16 1.8×	36	403
Tom Bagby United States	7	359 1.4×	245 1.1×	34 0.9×	16 0.9×	11 1.2×	7	402
Zhendong Peng China	8	269 1.1×	197 0.9×	29 0.7×	11 0.6×	15 1.7×	13	326
Sankaran Panchapagesan United States	9	322 1.3×	263 1.2×	38 1.0×	16 0.9×	11 1.2×	17	385
Jay Mahadeokar United States	8	324 1.3×	201 0.9×	23 0.6×	11 0.6×	4 0.4×	28	372
Hainan Xu United States	10	547 2.2×	298 1.4×	46 1.2×	8 0.5×	11 1.2×	22	585
Wayne Xiong United States	4	172 0.7×	86 0.4×	37 0.9×	21 1.2×	4 0.4×	5	234
Hardik B. Sailor India	9	257 1.0×	327 1.5×	78 2.0×	6 0.4×	6 0.7×	35	386
Vitaly Lavrukhin United States	6	312 1.2×	214 1.0×	44 1.1×	13 0.8×	6 0.7×	20	371

Countries citing papers authored by Zhongxin Bai

Since Specialization

Citations

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

Fields of papers citing papers by Zhongxin Bai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhongxin Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Zhongxin Bai. A scholar is included among the top collaborators of Zhongxin Bai 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 Zhongxin Bai. Zhongxin Bai 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.

Bai, Zhongxin, et al.. (2024). A Power-Domain Non-Orthogonal Integrated Sensing and Communication Waveform Design Using OFDM. IEEE Wireless Communications Letters. 13(4). 984–988. 5 indexed citations

2.

Zhou, Feng, et al.. (2024). MambaGAN: Mamba based Metric GAN for Monaural Speech Enhancement. 411–416. 2 indexed citations

3.

Bai, Zhongxin, et al.. (2022). End-to-End Speaker Verification via Curriculum Bipartite Ranking Weighted Binary Cross-Entropy. IEEE/ACM Transactions on Audio Speech and Language Processing. 30. 1330–1344. 23 indexed citations

4.

Bai, Zhongxin & Xiao-Lei Zhang. (2021). Speaker recognition based on deep learning: An overview. Neural Networks. 140. 65–99. 224 indexed citations breakdown →

5.

Bai, Zhongxin, Xiao-Lei Zhang, & Jingdong Chen. (2020). Speaker Verification by Partial AUC Optimization With Mahalanobis Distance Metric Learning. IEEE/ACM Transactions on Audio Speech and Language Processing. 28. 1533–1548. 13 indexed citations

6.

Bai, Zhongxin, Xiao-Lei Zhang, & Jingdong Chen. (2020). Partial AUC Optimization Based Deep Speaker Embeddings with Class-Center Learning for Text-Independent Speaker Verification. 6819–6823. 24 indexed citations

7.

Bai, Zhongxin, Xiao-Lei Zhang, & Jingdong Chen. (2020). Partial AUC Metric Learning Based Speaker Verification Back-End. 380–384. 4 indexed citations

8.

Bai, Zhongxin, Xiao-Lei Zhang, & Jingdong Chen. (2020). Cosine metric learning based speaker verification. Speech Communication. 118. 10–20. 6 indexed citations

9.

Bai, Zhongxin, et al.. (2019). AUC Optimization for Deep Learning Based Voice Activity Detection. 15 indexed citations

10.

Bai, Zhongxin, Xiao-Lei Zhang, & Jingdong Chen. (2018). Cosine Metric Learning for Speaker Verification in the I-vector Space. 1126–1130. 4 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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