Demo Data from EDBT 2026 / reviewers in the wild / expert
Yu Nishimura
dblp:297/2490
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0004-3978-6917ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 87% Ubiquitous computing and smart environments · 13% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input › input modality
silent speech interaction |
1.0 | 1 | 2026 | NasoVoce: A Nose-Mounted Low-Audibility Speech Interface for Always-Available Speech Interaction · CHI 2026 |
Interaction techniques and input › voice interaction
speech input |
1.0 | 1 | 2026 | NasoVoce: A Nose-Mounted Low-Audibility Speech Interface for Always-Available Speech Interaction · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
speech recognition · 1.0sensor fusion · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | NasoVoce: A Nose-Mounted Low-Audibility Speech Interface for Always-Available Speech InteractionabstractSilent and whispered speech offer promise for always-available voice interaction with AI, yet existing methods struggle to balance vocabulary size, wearability, silence, and noise robustness. We present NasoVoce, a nose-bridge–mounted interface that integrates a microphone and a vibration sensor. Positioned at the nasal pads of smart glasses, it unobtrusively captures both acoustic and vibration signals. The nasal bridge, close to the mouth, allows access to bone- and skin-conducted speech and enables reliable capture of low-volume utterances such as whispered speech. While the microphone captures high-quality audio, it is highly sensitive to environmental noise. Conversely, the vibration sensor is robust to noise but yields lower signal quality. By fusing these complementary inputs, NasoVoce generates high-quality speech robust against interference. Evaluation with Whisper Large-v2, PESQ, STOI, and MUSHRA ratings confirms improved recognition and quality. NasoVoce demonstrates the feasibility of a practical interface for always-available, continuous, and discreet AI voice conversations. Jun Rekimoto, Yu Nishimura, Bojian Yang |
CHI | 2 |