Hybrid Live: Preserving musical traditions and creating new practices performing over networks

Lead Research Organisation: Goldsmiths University of London
Department Name: Computing Department

Abstract

Hybrid Live is a collaboration between the Embodied AudioVisual Interaction (EAVI) unit at Goldsmiths and the Center for Computer Research in Music & Acoustics (CCRMA) at Stanford, in cooperation with cultural institutions Iklectik Art Lab (London) and SF Jazz (San Francisco). The project will mobilise advanced deep learning technologies and data visualization techniques in order to make remote, network based musical collaboration more fluid and ultimately musical for a broad range of musicians and music students. It will aid cultural institutions in music to respond to urgent issues raised by the COVID19 pandemic, and more generally broaden access and participation to live music. This will be made possible through an innovative hybrid of physically co-present and remote network musical performance, including a transatlantic connection between San Francisco and London.

Publications

10 25 50
 
Description We worked with Iklect Art Lab, Stanford University and SFJazz to develop technologies for low latency live music and dance performance. We presented two public events, Iklectika July 2022 and Distance Anatomy December 2022.
Exploitation Route Our tools are available for creative practitioners interested in network performance.
Sectors Creative Economy

 
Description We have organised two public events demonstrating long distance performance; The first at Iklectika in July 2022 connecting jazz musicians in London and San Francisco over the JackTrip low latency audio transport. The second, Distance Anatomy, where live visualization enabled us to transmit motion capture data of a dancer from New York over the network to the gig in London where the data was used in abstract visualization algorithms to generate an avatar in real time representing the dancer as they danced to electronic music performed in London and streamed over Jacktrip to New York.
First Year Of Impact 2022
Sector Creative Economy,Culture, Heritage, Museums and Collections
Impact Types Cultural

 
Description Iklectik Art Labs 
Organisation IKLECTIK
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution partnership with Local cultural institution, Iklectik Art Labs
Collaborator Contribution see above
Impact I sit on the board of advisors
Start Year 2019
 
Title Automatic avatar generator 
Description webcam visualizer of musician and dancer body movement for network transmission and visualization on receiving end using Google Mediapipe 
Type Of Technology Software 
Year Produced 2022 
Impact Used in Distance Anatomy performance connecting London and New York in Dec 2022 
 
Title FSK encoder for motion capture data onto audio carrier 
Description FSK encoder for motion capture data onto audio carrier 
Type Of Technology Software 
Year Produced 2022 
Impact FSK encoder for motion capture data onto audio carrier 
 
Description Distance Anatomy performance 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Network performance connecting London and New York using infrastructure and visualizer created in project. Electronic musicians in London collaborated live with dancers in New York with project technology generating live avatars in real time.
Year(s) Of Engagement Activity 2022
URL https://iklectikartlab.com/distance-anatomy/
 
Description Iklectika Festival 2022 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Network music concert connecting London (Iklectik) and San Francisco (SF JAzz) with three duos of jazz musicians colloborating over infrastructure created in the project
Year(s) Of Engagement Activity 2022
URL https://iklectikartlab.com/iklectikaliveactsanddjsets/