Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Anticipation in collaborative music performance using fuzzy systems: a case study (1906.02155v1)

Published 5 Jun 2019 in cs.AI

Abstract: In order to collaborate and co-create with humans, an AI system must be capable of both reactive and anticipatory behavior. We present a case study of such a system in the domain of musical improvisation. We consider a duo consisting of a human pianist accompained by an off-the-shelf virtual drummer, and we design an AI system to control the perfomance parameters of the drummer (e.g., patterns, intensity, or complexity) as a function of what the human pianist is playing. The AI system utilizes a model elicited from the musicians and encoded through fuzzy logic. This paper outlines the methodology, design, and development process of this system. An evaluation in public concerts is upcoming. This case study is seen as a step in the broader investigation of anticipation and creative processes in mixed human-robot, or "anthrobotic" systems.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Oscar Thörn (1 paper)
  2. Peter Fögel (1 paper)
  3. Peter Knudsen (1 paper)
  4. Luis de Miranda (1 paper)
  5. Alessandro Saffiotti (17 papers)
Citations (3)

Summary

We haven't generated a summary for this paper yet.