Shujie Liu
- Signal Processing top 0.2%
- Speech and Audio Processing 32
- Music and Audio Processing 30
- Artificial Intelligence top 0.2%
- Speech Recognition and Synthesis 62
- Natural Language Processing Techniques 60
- Topic Modeling 54
- Speech and dialogue systems 15
- Software top 5%
- Ocean Engineering top 1%
- Drilling and Well Engineering 14
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- Teacher Education and Leadership Studies 16
Shujie Liu
196 papers receiving 5.1k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Signal Processing 1.5k
- Artificial Intelligence 3.0k
- Computer Vision and Pattern Recognition 586
- Software 103
- Ocean Engineering 378
Countries citing papers authored by Shujie Liu
This map shows the geographic impact of Shujie Liu'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 Shujie Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shujie Liu more than expected).
Fields of papers citing papers by Shujie Liu
This network shows the impact of papers produced by Shujie Liu. 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 Shujie Liu. The network helps show where Shujie Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shujie Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Neural Codec Language Models are Zero-Shot Text to Speech Synthesizersbreakdown → | 2025 | 24 |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 18 | |
| 6 | 2024 | 2 | |
| 7 | 2022 | 26 | |
| 8 | 2021 | 7 | |
| 9 | 2021 | 112 | |
| 10 | UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data | 2021 | 14 |
| 11 | 2019 | 43 | |
| 12 | 2019 | 37 | |
| 13 | 2018 | 6 | |
| 14 | Evaluation technology for isolation capacity of cement sheath in HTHP high-sulfur gas wells | 2016 | 1 |
| 15 | 2015 | 99 | |
| 16 | 2013 | 11 | |
| 17 | 2013 | 15 | |
| 18 | Re-training Monolingual Parser Bilingually for Syntactic SMT | 2012 | 4 |
| 19 | Discriminative Pruning for Discriminative ITG Alignment | 2010 | 3 |
| 20 | Improved Discriminative ITG Alignment using Hierarchical Phrase Pairs and Semi-supervised Training | 2010 | 2 |
About Shujie Liu
Shujie Liu is a scholar working on Signal Processing, Artificial Intelligence, Medical Laboratory Technology, Ocean Engineering and Computer Vision and Pattern Recognition, having authored 211 papers that have together received 5.4k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (62 papers), Natural Language Processing Techniques (60 papers), Topic Modeling (54 papers), Speech and Audio Processing (32 papers), Music and Audio Processing (30 papers), Teacher Education and Leadership Studies (16 papers), Speech and dialogue systems (15 papers) and Drilling and Well Engineering (14 papers). The work is most often cited by research in Signal Processing (1.5k citations), Artificial Intelligence (3.0k citations), Computer Vision and Pattern Recognition (586 citations), Software (103 citations) and Ocean Engineering (378 citations). Shujie Liu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ming Zhou, Yu Wu, Anthony J. Onwuegbuzie, Jinyu Li, Chengyi Wang, Long Zhou, Shuo Ren, Sheng Zhao, Sanyuan Chen and Furu Wei. Their work appears in journals such as Ocean Engineering, IEEE/ACM Transactions on Audio Speech and Language Processing, Reliability Engineering & System Safety, Educational Assessment Evaluation and Accountability and Fuel.
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.