The purpose of this paper is to present an embodied view on human/machine co‐creation in general, and musical improvisation in particular.
Abstract
Purpose
The purpose of this paper is to present an embodied view on human/machine co‐creation in general, and musical improvisation in particular.
Design/methodology/approach
Questions and propositions are formed by examining personal work in intelligent, interactive system design.
Findings
Proper consideration of gestural representation and intentionality leads to enhanced potential for collective expression in human/machine interaction.
Originality/value
This approach extends ideas of conversation theory to improvisational contexts based on spontaneous, collective expression.
Details
Keywords
The purpose of this paper is to better understand communication between musicians in a free jazz improvisation in comparison to traditional jazz.
Abstract
Purpose
The purpose of this paper is to better understand communication between musicians in a free jazz improvisation in comparison to traditional jazz.
Design/methodology/approach
A cybernetic informative feedback model was used to study communication between musicians for free jazz. The conceptual model consists of the ears as sensors, an auditory analysis stage to convert the acoustic signals into symbolic information (e.g. notated music), a cognitive processing stage (to make decisions and adapt the performance to what is being heard), and an effector (e.g. muscle movement to control an instrument). It was determined which musical features of the co‐players have to be extracted to be able to respond adequately in a music improvisation, and how this knowledge can be used to build an automated music improvisation system for free jazz.
Findings
The three major findings of this analysis were: in traditional jazz a soloist only needs to analyze a very limited set of music ensemble features, but in free jazz the performer has to observe each musician individually; unlike traditional jazz, free jazz is not a strict rule‐based system. Consequently, the musicians need to develop their personal symbolic representation; which could be a machine‐adequate music representation for an automated music improvisation system. The latter could be based on acoustic features that can be extracted robustly by a computer algorithm.
Practical implications
Gained knowledge can be applied to build automated music improvisation systems for free jazz.
Originality/value
The paper expands our knowledge to create intelligent music improvisation algorithms to algorithms that can improvise with a free jazz ensemble.