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Sakamoto Lab
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A lab that develops and applies Kansei (affective) AI, using onomatopoeia as a key.
AboutAbout the lab
Advancing the development and application of Kansei AI.
The Sakamoto Lab studies the development and application of "Kansei AI," AI that deals with human sensibility and feelings.
The lab builds AI that expresses the texture of what it sees in onomatopoeia, and a system that detects signs of dementia using onomatopoeia.
It also works on supporting early diagnosis of diseases with LLMs, and on a spatial system in which AI estimates the atmosphere of a conversation.
Key terms
- Onomatopoeia
- Words that imitate sounds or describe states and sensations, such as "fuwafuwa" (fluffy) and "tsurutsuru" (smooth). This lab uses them as a key to putting texture into words
- LLM
- Large language model. This lab uses it to detect tendencies in patients' speaking style and vocabulary in everyday conversation
- Texture
- The impression, such as rough or smooth, that one feels when looking at an object. It is something AI finds difficult to express
ResearchResearch themes
The lab's research theme is the development and application of Kansei AI. Its work ranges from medical applications to the expression of texture and the quantification of the Kansei value of materials.
*Illustrative imageSupporting Early Disease Diagnosis with LLMs
The lab uses everyday physical and mental data to support the early diagnosis of conditions such as infectious diseases and dementia. For early diagnosis of HIV infection, it is pursuing a method that uses LLMs to detect tendencies in speaking style and vocabulary in everyday conversation.
*Illustrative imageDetecting Dementia Early with Onomatopoeia
The lab is developing a system that detects signs of dementia simply from people describing textures with onomatopoeia such as "fuwafuwa" (fluffy) and "tsurutsuru" (smooth). In collaboration with Juntendo University, it also evaluates the effectiveness of a game app.
*Illustrative imageAI That Expresses Texture with Onomatopoeia
The lab uses onomatopoeia to express texture, which is difficult for AI. It is building a model that learns the onomatopoeia produced by participants and, from an image, outputs texture expressions such as "tsurutsuru" (smooth) and "chikuchiku" (prickly) probabilistically.
*Illustrative imageA Platform for Measuring the Kansei Value of Materials
In collaboration with Kansei AI Inc., a startup that grew out of the lab, the lab provides the "Kansei Material Platform," which quantifies the Kansei value of materials. By integrating material data with human Kansei evaluations, it supports product development and material selection.
MembersFaculty
The members of the Sakamoto Lab are faculty, researchers, and doctoral, master's, and undergraduate students.As of 2025
- ProfessorMaki Sakamoto
- Project Associate ProfessorYuji Nozaki
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Denim fabric 05 (Rico Cilliers and colormass via Poly Haven)” Rico Cilliers (Processing) colormass (Photography) / CC0 (cropped)
- Supporting Early Disease Diagnosis with LLMs: “Pathologists looking into microscopes (1)” Linda Bartlett (Photographer) / Public domain (cropped)
- Detecting Dementia Early with Onomatopoeia: “Fluffy peaches” Fumikas Sagisavas / CC0 (cropped)
- AI That Expresses Texture with Onomatopoeia: “Dry wood texture” Martin Vorel / CC BY-SA 4.0 (cropped)
- A Platform for Measuring the Kansei Value of Materials: “Fabric samples from Salhus Væverier, Norway” Bevaringstenestene, Museumssenteret i Hordaland / CC BY-SA 4.0 (cropped)
- Related lab (水戸 和幸 研究室): “Muscle Whistler with EMG surface electrodes (1971)” Cromemco / CC BY-SA 3.0 (cropped)
- Related lab (柴田 淳司 研究室): “Robots and Kids” Draganzivancevic / CC BY-SA 4.0 (cropped)
- Related lab (児玉 幸子 研究室): “Ferrofluido PopArt” Gianlucas Bertone Corrado / CC BY-SA 4.0 (cropped)
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