Demo Data from VLDB 2026 / reviewers in the wild / expert
Andrea Conejo-Toledo
dblp:179/4881
· 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 |
Wearable and physiological sensing · 77% Accessibility and assistive technology · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Accessibility and assistive technology › assistive technology
wearable assistive device |
0.1 | 1 | 2016 | SayWAT: Augmenting Face-to-Face Conversations for Adults with Autism · CHI 2016 |
Methods — techniques the papers use, named apart from their topics
user study · 0.2design process · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | SayWAT: Augmenting Face-to-Face Conversations for Adults with AutismabstractDuring face-to-face conversations, adults with autism frequently use atypical rhythms and sounds in their speech (prosody), which can result in misunderstandings and miscommunication. SayWAT is a Wearable Assistive Technology that provides feedback to wearers about their prosody during face-to-face conversations. In this paper, we describe the design process that led to five design guidelines that governed the development of SayWAT and present results from two studies involving our prototype solution. Our results indicate that wearable assistive technologies can automatically detect atypical prosody and deliver feedback in real time without disrupting the wearer or the conversation partner. Additionally, we provide suggestions for wearable assistive technologies for social support. Louanne E. Boyd, Alejandro Rangel, Helen Tomimbang, Andrea Conejo-Toledo, Kanika Patel, Monica Tentori, Gillian R. Hayes |
CHI | 4 |