Demo Data from SIGIR 2026 / reviewers in the wild / expert
Idan Zelzer
dblp:179/4828
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
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 |
Accessibility and assistive technology · 50% Personal fabrication and tangible interfaces · 50% | |
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing › audio classification
sound classification |
0.1 | 1 | 2016 | Tickers and Talker: An Accessible Labeling Toolkit for 3D Printed Models · CHI 2016 |
Methods — techniques the papers use, named apart from their topics
signal processing · 0.5audio classification · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Tickers and Talker: An Accessible Labeling Toolkit for 3D Printed ModelsabstractThree-dimensional models are important learning resources for blind people. With advances in 3D printing, 3D models are becoming more available. However, unlike visual or tactile graphics, there is no standard accessible way to label components in 3D models. We present a labeling toolkit that enables users to add and access audio labels to 3D printed models. The toolkit includes Tickers, small 3D printed percussion instruments added to 3D models, and Talker, a signal processing application that detects and classifies Ticker sounds. To use the toolkit, a model designer adds Tickers to a model using 3D modeling software. A user then prints the model with Tickers and records audio labels for each Ticker. Finally, users can strum the Tickers and Talker will play the corresponding labels. We evaluated Tickers and Talker with three models in a study with nine blind participants. Our toolkit achieved an accuracy of 93% across all participants and models. We discuss design implications and future work for accessible 3D printed models. Lei Shi 0020, Idan Zelzer, Catherine Feng, Shiri Azenkot |
CHI | 2 |