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ROOM #81---Agent-Based Instrument for Experiencing Architectural and Vocal Cues

Nicolas d'Alessandro, Roberto Calderon, and Stefanie Müller

Proceedings of the International Conference on New Interfaces for Musical Expression

Abstract

ROOM#81 is a digital art installation which explores how visitors can interact with architectural and vocal cues to intimately collaborate. The main space is split into two distinct areas separated by a soft wall, i.e. a large piece of fabric tensed vertically. Movement within these spaces and interaction with the soft wall is captured by various kinds of sensors. People’s activity is constantly used by an agent in order to predict their actions. Machine learning is then achieved by such agent to incrementally modify the nature of light in the room and some laryngeal aspects of synthesized vocal spasms. The combination of people closely collaborating together, light changes and vocal responses creates an intimate experience of touch, space and sound.

Citation

Nicolas d'Alessandro, Roberto Calderon, and Stefanie Müller. 2011. ROOM #81---Agent-Based Instrument for Experiencing Architectural and Vocal Cues. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI: 10.5281/zenodo.1177933 [PDF]

BibTeX Entry


@inproceedings{nime2011_dAlessandro,
author = {d'Alessandro, Nicolas and Calderon, Roberto and Müller, Stefanie},
title = {ROOM #81---Agent-Based Instrument for Experiencing Architectural and Vocal Cues},
pages = {132--135},
booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
year = {2011},
address = {Oslo, Norway},
issn = {2220-4806},
doi = {10.5281/zenodo.1177933},
url = {https://nime.org/proceedings/2011/nime2011_132.pdf},
keywords = {agent,architecture,collaboration,figure 1,installation,instrument,interactive fabric,light,mo-,movements in the installation,space and,tion,voice synthesis},
abstract = {ROOM#81 is a digital art installation which explores how visitors can interact with architectural and vocal cues to intimately collaborate. The main space is split into two distinct areas separated by a soft wall, i.e. a large piece of fabric tensed vertically. Movement within these spaces and interaction with the soft wall is captured by various kinds of sensors. People’s activity is constantly used by an agent in order to predict their actions. Machine learning is then achieved by such agent to incrementally modify the nature of light in the room and some laryngeal aspects of synthesized vocal spasms. The combination of people closely collaborating together, light changes and vocal responses creates an intimate experience of touch, space and sound.}
}