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''Capacity:'' max. 12 students<br/> | ''Capacity:'' max. 12 students<br/> | ||
''Language:'' English<br/> | ''Language:'' English<br/> | ||
''Location:'' | ''Location:'' Online Stream and Material<br/> | ||
''First Meeting:'' ''' | ''First Meeting:'' '''tba''' | ||
==Description== | ==Description== | ||
Revision as of 20:59, 23 April 2020
Fachmodul
Acoustic Interfaces
Instructor: Clemens Wegener
Credits: 6 ECTS, 2 SWS
Capacity: max. 12 students
Language: English
Location: Online Stream and Material
First Meeting: tba
Description
We are constantly surrounded by electronic interfaces: elevators, automatic doors, ticket machines, remote controls, voice recognition systems, etc. With a high degree of networking between our devices, interfaces must seamlessly integrate into ecosystems of information acquisition and processing. Information acquisition and processing are becoming increasingly spatially separated. Thus, ergonomic sensor placement, which integrates discreetly into our accustomed environment, is gaining ground.
The course explores the possibilities of this ergonomic, embedded interaction using the example of acoustic interfaces. We will develop electronic sensor systems for the detection of vibrations (structure-borne sound) in integrated surfaces and experiment with machine learning methods to differentiate between vibration gestures (e.g. knocking noises, friction noises, etc.).
The Course will be taught in video sessions and regular assignments every two weeks.
If you are interested, please send a letter of motivation and portfolio to clemens.wegener ( at ) uni-weimar (dot) de.
Admission requirements
We will use either the Teensy 4.0 hardware platform or the Raspberry Pi to classify sounds in the environment. Therefore, a budget of (30-40€) should be planned for the Teensy and other components. Knowledge of programming is a requirement!
Evaluation
Successful completion of 50% of the assignments. Realization and documentation of a completed semester prototype and a final video presentation. Please refer to the Evaluation Rubric for more details.
Eligible participants
Qualified MFA Medienkunst/-gestaltung, MFA Media Art and Design, MSc MediaArchitecture candidates
Syllabus (subject to change)
Coming soon...
Course Material
Further Reading
Zamborlin, Bruno. 2015. Studies on customisation-driven digital music instruments. Doctoral thesis, Goldsmiths, University of London.
Murray-Smith, Roderick & Williamson, John & Hughes, Stephen & Quaade, Torben. (2008). Stane: Synthesized surfaces for tactile input. Conference on Human Factors in Computing Systems - Proceedings. 1299-1302. 10.1145/1357054.1357257.
Rasamimanana, N.H., Bevilacqua, F., Schnell, N., Guédy, F., Fléty, E., Maestracci, C., Zamborlin, B., Frechin, J., & Petrevski, U. (2010). Modular musical objects towards embodied control of digital music. Tangible and Embedded Interaction.
Pure Data Patches
Setting Up the Raspberry Pi
- You will need an SD card reader for Micro SD cards (eventually and SD card adapter)
- Download etcher and PatchboxOS
- Install balenaEtcher and launch
- Select downloaded PatchboxOS image and press flash
- Plug Your SD Card to the Raspberry Pi
- If you don't have a Raspberry Pi 3: Plug Your USB WIFI to the Raspberry
- Start it up!