Masao Utiyama
- Artificial Intelligence top 0.5%
- Natural Language Processing Techniques 164
- Topic Modeling 156
- Text Readability and Simplification 20
- Speech Recognition and Synthesis 19
- Speech and dialogue systems 16
- Semantic Web and Ontologies 14
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- Multimodal Machine Learning Applications 40
- Handwritten Text Recognition Techniques 15
- Language and Linguistics top 5%
- Information Systems top 5%
Masao Utiyama
176 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 111
- Artificial Intelligence 2.0k
- Computer Vision and Pattern Recognition 676
- Language and Linguistics 115
- Information Systems 139
- Catalysis 34
Countries citing papers authored by Masao Utiyama
This map shows the geographic impact of Masao Utiyama'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 Masao Utiyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masao Utiyama more than expected).
Fields of papers citing papers by Masao Utiyama
This network shows the impact of papers produced by Masao Utiyama. 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 Masao Utiyama. The network helps show where Masao Utiyama may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masao Utiyama, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2023 | 6 | |
| 4 | 2021 | 4 | |
| 5 | 2021 | 3 | |
| 6 | 2020 | 5 | |
| 7 | 2020 | 13 | |
| 8 | Neural Machine Translation with Universal Visual Representation | 2020 | 49 |
| 9 | An Empirical Study of Domain Adaptation for Unsupervised Neural Machine Translation. | 2019 | 2 |
| 10 | 2019 | 11 | |
| 11 | 2019 | 19 | |
| 12 | 2018 | 21 | |
| 13 | Introducing the Asian Language Treebank (ALT). | 2016 | 20 |
| 14 | Similar Southeast Asian Languages: Corpus-Based Case Study on Thai-Laotian and Malay-Indonesian. | 2016 | 1 |
| 15 | A Large-scale Study of Statistical Machine Translation Methods for Khmer Language | 2015 | 3 |
| 16 | 2014 | 22 | |
| 17 | Reordering Constraint Based on Document-Level Context | 2011 | 1 |
| 18 | Helping Volunteer Translators, Fostering Language Resources | 2010 | 1 |
| 19 | Toward the Evaluation of Machine Translation Using Patent Information | 2008 | 5 |
| 20 | Japanese Question-Answering System Using Decreased Adding with Multiple Answers at NTCIR 5. | 2005 | 3 |
About Masao Utiyama
Masao Utiyama is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Language and Linguistics, Information Systems and Computer Science Applications, having authored 193 papers that have together received 2.3k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (164 papers), Topic Modeling (156 papers), Multimodal Machine Learning Applications (40 papers), Text Readability and Simplification (20 papers), Speech Recognition and Synthesis (19 papers), Speech and dialogue systems (16 papers), Handwritten Text Recognition Techniques (15 papers) and Semantic Web and Ontologies (14 papers). The work is most often cited by research in Artificial Intelligence (2.0k citations), Computer Vision and Pattern Recognition (676 citations), Language and Linguistics (115 citations), Information Systems (139 citations) and Catalysis (34 citations). Masao Utiyama has collaborated with scholars based in Japan, China and Myanmar. Frequent co-authors include Eiichiro Sumita, Hitoshi Isahara, Rui Wang, Kehai Chen, Lemao Liu, Hai Zhao, Kiyotaka Uchimoto, Tiejun Zhao, Andrew Finch and Bao‐Liang Lu. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Language Resources and Evaluation, Machine Translation, Water Air & Soil Pollution and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.