VLDB 2026 Research / reviewers in the wild / expert
Stefani Allegretti
dblp:188/9036
· 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
Artificial intelligence and machine learning · 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.
| Artificial intelligence
1 paper |
Question answering and dialogue systems · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Question answering and dialogue systems
multi-party dialogue |
0.2 | 1 | 2016 | The Teams Corpus and Entrainment in Multi-Party Spoken Dialogues · EMNLP 2016 |
Natural language and speech › Question answering and dialogue systems
spoken dialogue |
0.2 | 1 | 2016 | The Teams Corpus and Entrainment in Multi-Party Spoken Dialogues · EMNLP 2016 |
Methods — techniques the papers use, named apart from their topics
acoustic-prosodic analysis · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | The Teams Corpus and Entrainment in Multi-Party Spoken DialoguesabstractWhen interacting individuals entrain, they begin to speak more like each other.To support research on entrainment in cooperative multi-party dialogues, we have created a corpus where teams of three or four speakers play two rounds of a cooperative board game.We describe the experimental design and technical infrastructure used to collect our corpus, which consists of audio, video, transcriptions, and questionnaire data for 63 teams (47 hours of audio).We illustrate the use of our corpus as a novel resource for studying team entrainment by 1) developing and evaluating teamlevel acoustic-prosodic entrainment measures that extend existing dyad measures, and 2) investigating relationships between team entrainment and participation dominance. Diane J. Litman, Susannah B. F. Paletz, Zahra Rahimi, Stefani Allegretti, Caitlin Rice |
EMNLP | 4 |