Trends at NIME -- Reflections on Editing "A NIME Reader"
October 21, 2020 Β· Declared Dead Β· π New Interfaces for Musical Expression
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Alexander Refsum Jensenius, Michael J. Lyons
arXiv ID
2010.10803
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.SD,
eess.AS
Citations
20
Venue
New Interfaces for Musical Expression
Last Checked
4 months ago
Abstract
This paper provides an overview of the process of editing the forthcoming anthology "A NIME Reader - Fifteen Years of New Interfaces for Musical Expression." The selection process is presented, and we reflect on some of the trends we have observed in re-discovering the collection of more than 1200 NIME papers published throughout the 15-year long history of the conference. An anthology is necessarily selective, and ours is no exception. As we present in this paper, the aim has been to represent the wide range of artistic, scientific, and technological approaches that characterize the NIME conference. The anthology also includes critical discourse, and through acknowledgment of the strengths and weaknesses of the NIME community, we propose activities that could further diversify and strengthen the field.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted