Best Paper Finalist award at 2019 IEEE/SICE International Symposium on System Integration
|On January 14-16, 2019, the IEEE/SICE International Symposium on System Integration (SII2019) was held. Among over 140 contributions, the paper of Daniel Gabriel (Tokyo Institute of Technology), Ryosuke Kojima (Kyoto University), Kotaro Hoshiba (Kanagawa University), Katsutoshi Itoyama (Tokyo Institute of Technology), Kenji Nishida (Tokyo Institute of Technology) and Kazuhiro Nakadai (Tokyo Institute of Technology, HRI-JP) entitled ‘Design and Assessment of Multiple-Sound Source Localization Using Microphone Arrays’ was chosen as one of five Best Paper Finalists. The awards were given based on the quality of the contribution and the written paper, as well as the quality of the oral presentation.|
Prince Shotoku robot was on the air
On Jan. 16, 2019, Prince Shotoku robot which can listen to simultaneous speech signals was introduced in the TV program of NHK E-tele.
The robot was developed by Honda Research Institute Japan Co., Ltd. with which Prof. Nakadai is working, and the robot audition technology was developed under the collaboration with Prof. Okuno, Waseda University (Honorary professor in Kyoto University).
In the program, the robot could listen to four simultaneous speech signals, but a movie for 11 simultaneous speech recognition is available here.
Prof. Nakadai received “Innovation generation award” from Ministry of Internal Affairs and Communications
|On October 24, 2018, the innovation program award ceremony of Ministry of Internal Affairs and Communications was held, and Professor Nakadai of the Department of Systems and Control Engineering, School of Engineering received Innovation Generation Award in the category of auditory technology for “Listening drone helps find victims needing rescue in disasters.”
The innovation program supports people who tackle ambitious ICT R&D challenges with tremendous possibilities to create destructive global values. It consists of the destructive innovation division and the innovation generation award division. In the Innovation Generation Award, there are 10,440 entries this year, and only 10 are awarded from 10 different fields.
14th HARK Tutorial at IEEE/RSJ IROS 2018
|We organized the 14th HARK (Honda Research Institute Japan Audition for Robots with Kyoto University) tutorial at IEEE/RSJ IROS 2018.
Thank you for many participants providing active discussions, many people who support software development and material preparation, and supportive societies and company such as RSJ, JSAI and HRI-JP.
Robot audition OS at IEEE/RSJ IROS 2018
|We organized Robot Audition OS at IEEE/RSJ IROS 2018. In total, 106 OS proposals were submitted, and only 14 were selected. This OS is one of the selected OS, and it has been successfully done with fruitful discussions.
Daniel Gabriel et al. received “International Session Best Paper Award” at 36th RSJ annual conference.
|Received “International Session Best Paper Award” at 36th RSJ annual conference for the paper entitled “Case study of bird localization via sound in 3D space” by Daniel Gabriel (Tokyo Institute of Technology), Ryosuke Kojima (Kyoto University), Kotaro Hoshiba (Kanagawa University), Katsutoshi Itoyama (Tokyo Institute of Technology), Kenji Nishida (Tokyo Institute of Technology), Kazuhiro Nakadai (Tokyo Institute of Technology, HRI-JP).|
Successfully organized IEEE Ro-MAN 2018 Workshop on Human-Robot Interaction through Virtual Reality (HRI-VR)
|We organized IEEE Ro-MAN 2018
Human-Robot Interaction through Virtual Reality (HRI-VR).
Through four insightful invited talks and another four presentations from authors who submitted to this workshop, the workshop was successfully held with fruitful discussions
Presented at the 27th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2018)
|Mr. Taniguchi presented “Signal Restoration Based on Bi-directional LSTM with Spectral Filtering for Robot Audition” at IEEE Ro-MAN 2018, which was held on Aug. 27-31, 2018 at Nanjing, China.|
’17年3月，名古屋大学で行われた「情報処理学会 第79回全国大会」にて，Daniel Gabriel君の発表が「学生奨励賞」に選ばれました．
Daniel Gabriel，小島諒介，干場功太郎（東工大），中臺一博（東工大/ホンダRIJ）:”Iterative Outlier Removal Method Using In-Cluster Variance Changes in Multi-Microphone Array Sound Source Localization.”
Our laboratory has been conducting researches mainly in Robot Audition and Environment Understanding since we started as Nakadai Laboratory in 2006.
In July 2017, we launched the next-generation AI robotics joint research laboratory with Honda Research Institute Japan Co., Ltd. (HRI-JP), and made a fresh start.
We are working on creating new fields that combine AI/Machine Learning, Robotics, Signal/Speech Processing in addition to core research in robot audition and scene analysis such as sound source localization, sound source separation, and automatic speech recognition.
For the benefits of joint research laboratory, we have a system that enables students who have been assigned to this laboratory to proceed in their researches not only in this university but also in HRI-JP. We operate our laboratory in cooperation with Imura Laboratory and Hayakawa Laboratory.