Demo Data from SIGIR 2026 / reviewers in the wild / expert
Sarah Kriz
dblp:35/5285
· DBLP profile ↗
6ranked-venue papers
5as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 4 first-authorHuman-computer interaction and ubiquitous computing · 5 · 4 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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
4 papers |
Human-robot interaction · 58% Collaborative and social computing · 20% Learning and educational technologies · 15% |
Topics — the 3 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › team collaboration › multilingual collaboration
linguistic adaptation |
0.1 | 1 | 2009 | Robot-directed speech as a means of exploring conceptualizations of robots · HRI 2009 |
Human-robot interaction › field robotics
human-robot interaction for search and rescue |
0.0 | 1 | 2010 | Robot rescue!: an HRI engineering outreach activity · HRI 2010 |
Human-AI interaction › large language model interaction › language-based interaction
natural language interface |
0.0 | 1 | 2010 | Robot-directed speech: using language to assess first-time users' conceptualizations of a robot · HRI 2010 |
Methods — techniques the papers use, named apart from their topics
speech analysis · 0.1script writing · 0.1comparative study · 0.1co-design · 0.1linguistic feature analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Robot-directed speech: using language to assess first-time users' conceptualizations of a robotabstractIt is expected that in the near-future people will have daily natural language interactions with robots. However, we know very little about how users feel they should talk to robots, especially users who have never before interacted with a robot. The present study evaluated first-time users' expectations about a robot's cognitive and communicative capabilities by comparing robot-directed speech to the way in which participants talked to a human partner. The results indicate that participants spoke more loudly, raised their pitch, and hyperarticulated their messages when they spoke to the robot, suggesting that they viewed the robot as having low linguistic competence. However, utterances show that speakers often assumed that the robot had humanlike cognitive capabilities. The results suggest that while first-time users were concerned with the fragility of the robot's speech recognition system, they believed that the robot had extremely strong information processing capabilities. Sarah Kriz, Gregory Anderson 0002, J. Gregory Trafton |
HRI | 1 |
| 2010 | Robot rescue!: an HRI engineering outreach activityabstractThis video is an example of an engineering outreach activity that we designed to illustrate some of the core issues in HRI research. High school students attending the University of Washington 2009 Summer Math Academy were given a disaster scenario and were asked think about how a robot could help a victim who was trapped by fallen rubble during an earthquake. Students were led through a series of thought questions that encouraged them to consider the type of information the robot would need to give to the victim, the victim's family, and the rescue team. They also considered how a victim might respond to a robot, and the behaviors the robot should display during the rescue. The students then created a script for the rescue scenario, writing not only their own lines, but the behavior and communication of the robot as well. All relevant consent forms were obtained from the participants prior to the outreach event. Jonathan T. Morgan, Sarah Kriz |
HRI | 2 |
| 2010 | Fictional robots as a data source in HRI research: Exploring the link between science fiction and interactional expectationsabstractBecause interacting with a robot is a novel experience for most adults, expectations about a robot's capabilities must come from sources other than past experiences. This paper explores the relationship between capabilities of robots portrayed in popular science fiction films and students' expectations about a real robot. A content analysis of 12 American science fiction films showed that fictional robots reliably display cognitive capabilities, but do not consistently exhibit many humanlike social behaviors. Survey data collected from students follow the same basic patterns: people expect robots to have humanlike cognitive capabilities, but not social capabilities. The results are discussed in terms of how an empirical evaluation of cultural artifacts can inform the study of human-robot interaction. Sarah Kriz, Toni Ferro, Pallavi Damera, John R. Porter |
RO-MAN | 1 |
| 2009 | Robot-directed speech as a means of exploring conceptualizations of robotsabstractDecades of research have shown that speakers adapt the way in which they speak to meet the needs of listeners, and that speech modifications can illuminate speakers' conceptualizations of their listeners' cognitive and communicative abilities. The present study extends this line of research into human-robot communication by analyzing the linguistic features of commands given to a robotic dog. The results indicate that males and females differed in the way in which they spoke to the robot, suggesting that there was not a uniform expectation of the robot's communicative capacities. Sarah Kriz, Gregory Anderson 0002, Magdalena D. Bugajska, J. Gregory Trafton |
HRI | 1 |
| 2007 | Top-down and bottom-up influences on learning from animations
Sarah Kriz, Mary Hegarty |
Int. J. Hum. Comput. Stud. | 1 |
| 2002 | Understanding Simultaneity and Causality in Static Diagrams versus Animation
Sarah Kriz |
Diagrams | 1 |