Hidden Sounds

Hidden Sounds

Jenny Gräf, Eva Sjuve, Katja Serber, Andreas Oxenvad, Nanna Hauge, Valdemar Kristensen, Stephen McEvoy

The Hidden Sounds research group is  interested in sounds that are out of reach of human hearing, but that may still have an impact on the body. To achieve this, they have been building tools that are able to pick up electro-magnetic frequencies, such as the Tesla Spirit Radio (crystal diode radio), and complementing them with building a variety of antennae using different design principles.

Antenna Creation

In June – August, 2018 the group built a variety of antennae in order to learn more about the unseen electromagnetic energy surrounding us.  Included in these activities was the creation of two Tesla Spirit Radios and a vlf copper wire loop antenna. These are being used in a variety of locations to listen to electromagnetic energy/activity such as particles from the sun hitting our atmosphere, natural and man-generated radio, wifi signals and other electromagnetic waves that surround us. The group has been making recordings of these  signals as they are sonified via the antenna.

Research Questions:

What are some interesting tools for creative use that pick up on electro-magnetic spectrums?

How to interpreting and making meaning from these inaudible communications?

Can these tools be folded back onto the body or interact with the body or?

Can we, for example, detect interference of the body with this spectrum?

How to measuring the electromagnetic fields?

Can trees act as antennae. What can we learn about trees as telecommunicators?

Text: 

Earth Sound Earth Signal: Energies and Earth Magnitude in the Arts, by Douglas Kahn, 2013.

Eva Sjuve — Metopia Deep (Signal)

Metopia Deep (Signal) by Eva Sjuve, is an interface to sense signals from WiFi and mobile phones in our environment, signals invisible to our visible perception. The signals are sensed through a sound composition of utterances in rhythmic patterns from the voice of Nuria Divi (NYC), using sonification techniques and machine learning to activate the listener to explore their environment.