Demo Data from SIGIR 2026 / reviewers in the wild / expert
Toby Gifford
dblp:132/1513
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-9902-3362ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2Applied, interdisciplinary, general and emerging computing · 2
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 |
Human-AI interaction · 50% Haptics and multimodal interaction · 50% | |
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction
creative AI |
0.4 | 1 | 2019 | In a Silent Way: Communication Between AI and Improvising Musicians Beyond Sound · CHI 2019 |
Audio and music processing
music generation |
0.1 | 1 | 2019 | In a Silent Way: Communication Between AI and Improvising Musicians Beyond Sound · CHI 2019 |
Methods — techniques the papers use, named apart from their topics
skin conductance sensing · 0.8FSS-2 questionnaire · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | In a Silent Way: Communication Between AI and Improvising Musicians Beyond SoundabstractCollaboration is built on trust, and establishing trust with a creative Artificial Intelligence is difficult when the decision process or internal state driving its behaviour isn't exposed. When human musicians improvise together, a number of extra-musical cues are used to augment musical communication and expose mental or emotional states which affect musical decisions and the effectiveness of the collaboration. We developed a collaborative improvising AI drummer that communicates its confidence through an emoticon-based visualisation. The AI was trained on musical performance data, as well as real-time skin conductance, of musicians improvising with professional drummers, exposing both musical and extra-musical cues to inform its generative process. Uni- and bi-directional extra-musical communication with real and false values were tested by experienced improvising musicians. Each condition was evaluated using the FSS-2 questionnaire, as a proxy for musical engagement. The results show a positive correlation between extra-musical communication of machine internal state and human musical engagement. Jon McCormack, Toby Gifford, Patrick Hutchings, Maria Teresa Llano, Matthew Yee-King, Mark d'Inverno |
CHI | 2 |
| 2017 | Distributed Musical Decision-making in an Ensemble of Musebots : Dramatic Changes and Endings A Brief History of Musebot Ensembles
Arne Eigenfeldt, Oliver Bown, Andrew R. Brown, Toby Gifford |
ICCC | 4 |
| 2016 | Flexible Generation of Musical Form: Beyond Mere Generation
Arne Eigenfeldt, Oliver Bown, Andrew R. Brown, Toby Gifford |
ICCC | 4 |
| 2013 | Factors affecting audience perceptions of agency in human computer musical partnershipsabstractWhat design factors contribute to an illusion of agency in a computational system? Our previous research [1, 2] has investigated this question in the context of creative human-machine musical partnerships, where we identified musical behaviours implying machine agency from the perspective of a human performer. This paper investigates an audience perspective: what factors contribute to an impression of machine agency for in a musical performance? Audience feedback data was collected during a concert with four performances, each comprising a human musician interacting with a computer music system. Three performances utilized a computational agent, CIM [1], designed for this research. The fourth performance utilized an array of effect pedals designed in an extended instrument paradigm [3]. The audience feedback questionnaire queried whether a sense of machine agency was imparted, and to what degree visual, spatial, timbral and musical factors contributed to this impression. The results showed our CIM system succeeded in imparting a sense of agency, and that all four of the suggested factors contributed to that impression. Andrew R. Brown, Toby Gifford, Bradley Voltz |
Creativity & Cognition | 2 |