Member Highlights: Satoshi Nakamura

Satoshi Nakamura received his B.S. degree in electronics engineering from Kyoto Institute of Technology, Kyoto, in 1981. He received his Ph.D. in informatics from Kyoto University in 1992. He was the Department Head and Director of ATR Spoken Language Communication Research Laboratories, Kyoto, Japan in the period of 2000-2008. He was the Director-General of Keihanna Research Laboratories and Executive Director of Knowledge-Creating Communication Research Center, National Institute of Information and Communications Technology in 2009-2010. He is currently the director of Data Science Center and full professor of Augmented Human Communication Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology. He is also the Team Leader of the Tourism Information Analytics Team at Center for Advanced Intelligence Project (AIP) Center, RIKEN, and Honorary Professor at Karlsruhe Institute of Technology, Germany. His research interests include modeling and developing systems of spoken language processing, speech processing, natural language processing, and data science. He is one of the world leaders in speech-to-speech translation research and has been serving in a wide range of research projects in that field. He published more than 120 peer-reviewed academic journals and 500 peer-reviewed international conference papers. He was awarded various international and domestic awards including the ELRA Antonio Zampolli Prize and commendation for science and technology by the Minister of Education, Culture, Sports, Science and Technology, Japan. He was an elected Board Member of the International Speech Communication Association, ISCA, in the period of June 2011-2019, an IEEE Signal Processing Magazine Editorial Board member in 2012-2015, and IEEE SPS Speech and Language Technical Committee Member in 2013-2015. He is ATR Fellow, IPSJ Fellow, ISCA Fellow, and IEEE Fellow.
We approached Satoshi Nakamura with a few questions:
1. Why did you choose to become faculty in the field of Signal Processing?
2. How does your work affect society?
We at ATR established an international consortium for speech translation called CSTAR, Consortium for Speech Translation Advanced Research, collaborated with US, EU, and Asian research institutions in early ‘90. Later this consortium started an International Workshop on Spoken Language Translation, IWSLT, in 2004. The IWSLT also started various shared tasks to enhance the development of speech translation-related research.
In Japan, the speech translation technologies developed at ATR and NICT have been licensed to various industries and deployed to various services, including speech translation services for inbound and outbound tourists. It is expected that further research on the automatic speech interpretation technologies will help online speech interpretation services and speech dubbing of multiple languages.
3. What challenges have you had to face to get where you are today?
- The most difficult part of my research was to ensure sustainable research funds and to keep excellent research colleagues. It was nice to have lots of motivated graduate students at NAIST but they left the lab after graduation. In the long run, the graduates could be a strong competitor. Another difficulty was that research laboratories such as ATR and NICT are not able to provide sufficient tenure researcher positions.
- The second challenge was to find where to work. I was lucky because I had chances to move when I needed to move. We have to find an optimal place to work on what we want to do. Accumulating small successes when young is very useful to find the next position for new research.
- The balance between novelty and performance. The continuous improvements bring solid performance and more publications, both of which are inevitable to survive in the world of research. On the other hand, innovative idea does not always bring better performance compared to the existing state-of-the-art systems. Only a good combination of novelty and performance can create a breakthrough to a new paradigm. I prefer to work on innovative idea, but it takes time especially for preparing original primal data and new evaluation metrics. The workload is much heavier while the chance rate of success is lower. I would say that the balance of these two is a very difficult problem.
4. What advice would you give to scientists/engineers in signal processing?
5. Anything else that you would like to add?
To learn more about Satoshi Nakamura and for more information, visit his webpage.