Cheng-I Lai

1.6k total citations · 2 hit papers
14 papers, 875 citations indexed

About

Cheng-I Lai is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Cheng-I Lai has authored 14 papers receiving a total of 875 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 6 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Cheng-I Lai's work include Speech Recognition and Synthesis (10 papers), Natural Language Processing Techniques (9 papers) and Topic Modeling (6 papers). Cheng-I Lai is often cited by papers focused on Speech Recognition and Synthesis (10 papers), Natural Language Processing Techniques (9 papers) and Topic Modeling (6 papers). Cheng-I Lai collaborates with scholars based in United States, Taiwan and Japan. Cheng-I Lai's co-authors include James Glass, Nanxin Chen, Yuan Gong, Yu-An Chung, Hung-yi Lee, Yung-Sung Chuang, Jesús Villalba, Najim Dehak, Shang-Wen Li and Shinji Watanabe and has published in prestigious journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Proceedings of the AAAI Conference on Artificial Intelligence and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

In The Last Decade

Cheng-I Lai

13 papers receiving 830 citations

Hit Papers

SUPERB: Speech Processing Universal PERformance Benchmark 2021 2026 2022 2024 2021 2022 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheng-I Lai United States 10 718 567 104 80 29 14 875
Brecht Desplanques Belgium 9 819 1.1× 737 1.3× 85 0.8× 50 0.6× 32 1.1× 20 1.0k
Jenthe Thienpondt Belgium 6 792 1.1× 704 1.2× 75 0.7× 42 0.5× 32 1.1× 13 894
Xuankai Chang United States 21 1.4k 1.9× 1.1k 1.9× 72 0.7× 88 1.1× 25 0.9× 66 1.6k
Jiatong Shi United States 13 807 1.1× 497 0.9× 63 0.6× 93 1.2× 20 0.7× 50 950
Longbiao Wang China 16 603 0.8× 623 1.1× 89 0.9× 139 1.7× 50 1.7× 62 771
Shinnosuke Takamichi Japan 16 756 1.1× 682 1.2× 115 1.1× 64 0.8× 33 1.1× 116 978
Sachin Kajarekar United States 20 1.3k 1.8× 1.2k 2.1× 119 1.1× 84 1.1× 19 0.7× 52 1.4k
Tsubasa Ochiai Japan 7 897 1.2× 681 1.2× 71 0.7× 45 0.6× 26 0.9× 11 1.0k
Kushal Lakhotia Israel 10 830 1.2× 456 0.8× 94 0.9× 93 1.2× 30 1.0× 11 950
František Grézl Czechia 20 1.5k 2.1× 1.3k 2.2× 127 1.2× 74 0.9× 16 0.6× 48 1.6k

Countries citing papers authored by Cheng-I Lai

Since Specialization
Citations

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

Fields of papers citing papers by Cheng-I Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheng-I Lai. 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 Cheng-I Lai. The network helps show where Cheng-I Lai may publish in the future.

Co-authorship network of co-authors of Cheng-I Lai

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

All Works

14 of 14 papers shown
1.
Lai, Cheng-I, et al.. (2023). Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken Sentences. 1–5. 1 indexed citations
2.
Lai, Cheng-I, Freda Shi, Yoon Kim, et al.. (2023). Audio-Visual Neural Syntax Acquisition. 1–8.
3.
Liu, Alexander, et al.. (2022). Cross-Modal Discrete Representation Learning. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 3013–3035. 24 indexed citations
4.
Lai, Cheng-I, Erica Cooper, Yang Zhang, et al.. (2022). On the Interplay between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8447–8451. 3 indexed citations
5.
Lai, Cheng-I, et al.. (2022). Simple and Effective Unsupervised Speech Synthesis. Interspeech 2022. 843–847. 9 indexed citations
6.
Gong, Yuan, Cheng-I Lai, Yu-An Chung, & James Glass. (2022). SSAST: Self-Supervised Audio Spectrogram Transformer. Proceedings of the AAAI Conference on Artificial Intelligence. 36(10). 10699–10709. 146 indexed citations breakdown →
7.
Yang, Shu-Wen, Po-Han Chi, Yung-Sung Chuang, et al.. (2021). SUPERB: Speech Processing Universal PERformance Benchmark. 1194–1198. 409 indexed citations breakdown →
8.
Lai, Cheng-I, Yung-Sung Chuang, Hung-yi Lee, Shang-Wen Li, & James Glass. (2021). Semi-Supervised Spoken Language Understanding via Self-Supervised Speech and Language Model Pretraining. 7468–7472. 35 indexed citations
9.
Cooper, Erica, Cheng-I Lai, Yusuke Yasuda, et al.. (2020). Zero-Shot Multi-Speaker Text-To-Speech with State-Of-The-Art Neural Speaker Embeddings. 6184–6188. 98 indexed citations
11.
Cooper, Erica, Cheng-I Lai, Yusuke Yasuda, & Junichi Yamagishi. (2020). Can Speaker Augmentation Improve Multi-Speaker End-to-End TTS?. 3979–3983. 14 indexed citations
12.
Lai, Cheng-I, Nanxin Chen, Jesús Villalba, & Najim Dehak. (2019). ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual Networks. 1013–1017. 102 indexed citations
13.
Guo, Jialiang, et al.. (2019). Controlling the Reading Level of Machine Translation Output. 193–203. 15 indexed citations
14.
Nidadavolu, Phani Sankar, Cheng-I Lai, Jesús Villalba, & Najim Dehak. (2018). Investigation on Bandwidth Extension for Speaker Recognition. 1111–1115. 11 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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