Dr. Naoki Kimura
I research human–computer interaction: how people interact with computing systems. My work includes silent speech interfaces, wearable text entry, and immersive visual experiences. Representative projects include SilentSpeller, SottoVoce, and 3-Key-Input.
木村 直紀（Naoki Kimura）は、人とコンピューターの関わりを研究しています。声を出さずに文字を入力する仕組みや、 身につけて使う入力装置、視野を広げる映像体験が研究テーマです。 代表研究と論文一覧をご覧いただけます。
View CV · Email for research enquiries · All publications
Literature resources: silent-speech paper reviews and CHI 2026 reviews.
Personal and research profile
Naoki Kimura is Chief Research Scientist at Yahoo. He received his Ph.D. in Information Studies from The University of Tokyo, where he was advised by Jun Rekimoto and Thad Starner. This site is his personal and research homepage.
Email for research enquiries · View CV · GitHub profile · HCI Reviews · Publications
Research areas
Silent speech interaction
Interfaces for entering text or controlling voice-operated devices without speaking aloud, using tongue-contact sensing or ultrasound imaging.
SilentSpeller research and evidence · SottoVoce research and evidence
Wearable and reduced-key text entry
Research on hands-free silent spelling and the possibilities and limits of text entry with fewer physical keys.
Immersive visual experiences
ExtVision and Deep Dive explore generating or extending images and video for peripheral vision and head-mounted displays.
Representative research
Research publications authored or co-authored by Naoki Kimura. Follow the paper links for the original methods and evaluations.
Rank-Residual Coding with a Shared Decoder: Lossless Low-Bit Communication for Ambiguous-Keyboard AAC
Forthcoming at IEEE SLT 2026 (accepted).
3-Key-Input: Exploring the Theoretical Minimum Keys for Text Entry
This work evaluates how far physical keyboards can be reduced when language-model-based disambiguation is used, finding that three keys can serve as a practical minimum in the evaluated offline English text-entry setting.
SilentSpeller: Towards mobile, hands-free, silent speech text entry using electropalatography
SilentSpeller reframes silent speech as silent spelling so that a wearable tongue-sensing retainer can support larger vocabularies, unseen words, and live text entry while walking.
SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks
SottoVoce uses ultrasound imaging under the jaw to regenerate speech audio, letting an unchanged smart speaker stack handle recognition instead of building a bespoke end-to-end SSI product.
More selected publications
Gaze+Lip: Rapid, Expressive Interactions Combining Gaze Input and Silent Speech Commands for Hands-free Smart TV Control
ETRA 2021
Mobile, Hands-free, Silent Speech Texting Using SilentSpeller
CHI 2021 Interactivity
CHI 2021 publication (DOI) · CHI 2021 paper (PDF, co-author's site)
SonoSpace: Visual Feedback of Timbre with Unsupervised Learning
SonoSpace maps instrumental timbre into a two-dimensional latent space so learners can compare their sound to expert performances without relying on verbal teacher feedback.
Expert reviews of silent-speech interaction
The silent-speech paper review database covers work by many research groups, including reviews of my own papers below. It is a literature resource, not my publication list. The CHI 2026 review collection covers a broader range of human–computer interaction research.
New to this literature? Start with three silent-speech reviews before exploring the full database.
初めて読む方は、サイレントスピーチの読み始め：まず3本のレビューからどうぞ。
SilentSpeller: Towards mobile, hands-free, silent speech text entry using electropalatography
SilentSpeller is a strong, rigorously tested SSI system that reframes silent speech as silent spelling, enabling large vocabulary, live text entry, and walking robustness with in-mouth electropalatography sensors.
SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks
A solid proof of concept that reconstructs speech audio from ultrasound for controlling unmodified smart speakers, showcasing important system design insight despite prototype limitations in latency, hardware bulk, and speaker dependency.
Education
Ph.D. in Information Studies, The University of Tokyo
Graduate School of Interdisciplinary Information Studies. Advisors: Jun Rekimoto and Thad Starner.
Master's degree with highest distinction, The University of Tokyo
Information Studies, Graduate School of Interdisciplinary Information Studies.
BA in Urban Engineering, The University of Tokyo
Honors
Official announcements and project reports are linked where available so you can check the research record.
Microsoft Research Asia D-CORE
Winner.
JSPS Research Fellowship for Young Scientists DC2
Research fellowship noted in the 2021 CV.
JST ACT-X
Frontier of mathematics and information science.
Google PhD Fellowship
Winner.
ACM CHI Honorable Mention Award
For SottoVoce, top 5%.