Yao Qian

5.6k total citations · 2 hit papers
144 papers, 3.2k citations indexed

About

Yao Qian is a scholar working on Artificial Intelligence, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Yao Qian has authored 144 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Artificial Intelligence, 59 papers in Signal Processing and 13 papers in Experimental and Cognitive Psychology. Recurrent topics in Yao Qian's work include Speech Recognition and Synthesis (84 papers), Speech and Audio Processing (54 papers) and Natural Language Processing Techniques (38 papers). Yao Qian is often cited by papers focused on Speech Recognition and Synthesis (84 papers), Speech and Audio Processing (54 papers) and Natural Language Processing Techniques (38 papers). Yao Qian collaborates with scholars based in China, United States and Hong Kong. Yao Qian's co-authors include Frank K. Soong, Yuchen Fan, Fenglong Xie, Chengyi Wang, Wenping Hu, Shujie Liu, Yu Wu, Michael Zeng, Jinyu Li and Zhengyang Chen and has published in prestigious journals such as Analytical Chemistry, Chemosphere and IEEE Transactions on Power Systems.

In The Last Decade

Yao Qian

141 papers receiving 2.9k 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.

WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

2022 832 citations Chengyi Wang, Yu Wu et al. profile →
TTS synthesis with bidirectional LSTM based recurrent neural networks

2014 286 citations Yuchen Fan, Yao Qian et al. profile →

Peers

Yao Qian

AI

SP

ECP

CVPR

PHYSI

Arnab Ghoshal United States

Zhen-Hua Ling China

Kai Yu China

Xiong Xiao Singapore

Ismail Shahin United Arab Emirates

Daniel Park United States

Vikramjit Mitra United States

Tan Lee Hong Kong

Heiga Zen Japan

Erik McDermott Japan

Arnab Ghoshal United States

Yao Qian

2.2k ×0.8

AI

1.7k ×1.0

SP

311 ×0.7

ECP

348 ×1.4

CVPR

68 ×1.1

PHYSI

Citations per year, relative to Yao Qian Yao Qian (= 1×) peers Arnab Ghoshal

Countries citing papers authored by Yao Qian

Since Specialization

Citations

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

Fields of papers citing papers by Yao Qian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yao Qian

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

Liu, Gang, et al.. (2025). PSO-MLSt-LSTM: Multi-layer stacked ensemble model for lithium-ion battery SOH prediction via multi-feature fusion. Journal of Energy Storage. 125. 116825–116825. 2 indexed citations

2.

Qian, Yao, et al.. (2025). Identification of SNAT Gene Family and Their Response to Abiotic Stress in Citrus. Horticulturae. 11(4). 399–399. 2 indexed citations

3.

Wang, Xiaofei, Chu‐Chieh Lin, Linjie Li, et al.. (2025). Audio-Aware Large Language Models as Judges for Speaking Styles. 467–480.

4.

Yang, Ziyi, Mahmoud Khademi, Xu Yi‐chong, et al.. (2024). i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data. 1615–1627. 2 indexed citations

5.

Qian, Yao, et al.. (2024). Molecular mechanisms underlying the negative effects of transient heatwaves on crop fertility. Plant Communications. 5(9). 101009–101009. 11 indexed citations

6.

Shi, Liang, Shijie Zhang, Yao Qian, et al.. (2023). Ectomycorrhizal fungi, two species of Laccaria, differentially block the migration and accumulation of cadmium and copper in Pinus densiflora. Chemosphere. 334. 138857–138857. 6 indexed citations

7.

Xu, Rui, et al.. (2022). Multiscale feature pyramid network based on activity level weight selection for infrared and visible image fusion. Journal of the Optical Society of America A. 39(12). 2193–2193. 3 indexed citations

8.

Wang, Rui, Long Zhou, Chengyi Wang, et al.. (2022). SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 5723–5738. 70 indexed citations

9.

Hussain, Mubasher, Yao Qian, Yu Zhong, et al.. (2022). Effects of novel cellulase (Cel 906) and probiotic yeast fermentation on antioxidant and anti-inflammatory activities of vine tea (Ampelopsis grossedentata). Frontiers in Bioengineering and Biotechnology. 10. 1006316–1006316. 8 indexed citations

10.

Wang, Chengyi, Yu Wu, Yao Qian, et al.. (2021). UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data. International Conference on Machine Learning. 10937–10947. 14 indexed citations

11.

Chen, Wei, et al.. (2021). P‐1.3: Development of an 11.6‐inch 144Hz LCD Utilizing an IGZO TFT Backplane. SID Symposium Digest of Technical Papers. 52(S1). 420–422. 2 indexed citations

12.

Wang, Pengyu, et al.. (2020). Bending Mechanical Model of Transverse Joints in Precast Prestressed Municipal Tunnel and Its Value Method. Journal of Northeastern University. 41(5). 629. 1 indexed citations

13.

Fan, Yuchen, Yao Qian, Frank K. Soong, & Lei He. (2016). Speaker and language factorization in DNN-based TTS synthesis. 5540–5544. 22 indexed citations

14.

Hu, Wenping, Yao Qian, & Frank K. Soong. (2015). An improved DNN-based approach to mispronunciation detection and diagnosis of L2 learners’ speech. 71–76. 25 indexed citations

15.

Lei, Ming, Yao Qian, Frank K. Soong, et al.. (2015). Modeling F0 trajectories in hierarchically structured deep neural networks. Speech Communication. 76. 82–92. 14 indexed citations

16.

Qian, Yao, Zhijie Yan, Yi-Jian Wu, et al.. (2010). An HMM Trajectory Tiling (HTT) Approach to High Quality TTS - Microsoft Entry to Blizzard Challenge 2010. 102–106. 6 indexed citations

17.

Qian, Yao, Houwei Cao, & Frank K. Soong. (2008). HMM-Based Mixed-Language (Mandarin-English) Speech Synthesis. 13–16. 4 indexed citations

18.

Liang, Hui, Yao Qian, & Frank K. Soong. (2007). An HMM-based bilingual (Mandarin-English) TTS.. SSW. 137–142. 13 indexed citations

19.

Lee, Tan & Yao Qian. (2005). Use of tone information in cantonese lvcsr based on generalized character posterior probability decoding. 19(4). 457–61. 5 indexed citations

20.

Qian, Yao, et al.. (2002). Prosodic word: the lowest constituent in the Mandarin prosody processing. 591–594. 6 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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