The Media Information Laboratory is organized into five research groups: media recognition, signal processing, computational modeling, biomedical informatics, and computing theory. We are promoting basic researches on information processing technology and fundamental principles related to "media", which is a medium for transmitting information in communication.
"Media" is a medium for transmitting information in communication among people or between people and computers. It can also be regarded as data obtained by observing various information in the real world and virtual world. Based on this idea, not only sounds and images that can be observed through sight and hearing, various observable data from real and cyber worlds can be subject to media information processing.
In this way, we take a broader view of the state of media information processing. We are aiming to approach the fundamental principle of communication and to develop technologies that enrich our lives in the real world and virtual world --- by bringing together the experience and knowledge of experts in a wide range of fields such as real-world measurement, modeling, signal processing, media recognition understanding, media generation, and the basic mathematical theories and algorithms that support them.
[Award] Tsubasa Ochiai has received The 16th Itakura Prize Innovative Young Researcher Award from the Acoustical Society of Japan.
"Joint Optimization of Microphone Array Signal Processing and Speech Recognition"
[Award] Hirokazu Kameoka has received The 10th RIEC Award from Research Institute of Electrical Communication Tohoku University.
"Audio Signal Decomposition and Scene Analysis"
Rintaro Ikeshita has received the 49th Awaya Kiyoshi Science Promotion Award from the Acoustical Society of Japan.
Rintaro Ikeshita and Tomohiro Nakatani, "Multiplicative update algorithms for independent vector analysis," 2020 Autumn meeting of Acoustical Society of Japan, 1-1-13, 2020.
Onkar Krishna, Go Irie, Xiaomeng Wu, Takahito Kawanishi and Kunio Kashino has received a "Best Research Paper Award Honorable Mention"
at the 26th Symposium on Sensing via Image Information.
Onkar Krishna, Go Irie, Xiaomeng Wu, Takahito Kawanishi and Kunio Kashino(2020). "Adaptive Spotting: 3D Point Cloud Object Search Based on Deep Reinforcement Learning," The 26th Symposium on Sensing via Image Information.
Last Update: 11/8/2022