id |
caadria2021_415 |
authors |
Chuang, Cheng-Lin and Chien, Sheng-Fen |
year |
2021 |
title |
Facilitating Architect-Client Communication in the Pre-design Phase |
doi |
https://doi.org/10.52842/conf.caadria.2021.2.071
|
source |
A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 71-80 |
summary |
The process of architects exploring the program with clients often take place through face-to-face oral discussions and visual aids, such as photos and sketches. Our research focuses on two communication mediums: language and sketch. We employ machine learning techniques to assist architects and clients to improve their communication and reduce misunderstandings. We have trained a Naive Bayesian Classifier machine, the language assistant (LA), to classify architectural vocabularies with associations to design requirements. In addition, we have trained a Generative Adversarial Network, the sketch assistant (SA), to generate photo quality images based on architects' sketches. The language assistant and sketch assistant combined can facilitate architect-client communication during the pre-design stage. |
keywords |
Architect-Client Communication; Pre-design; Architectural Programming; Machine Learning; Schematic Design |
series |
CAADRIA |
email |
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full text |
file.pdf (9,121,002 bytes) |
references |
Content-type: text/plain
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last changed |
2022/06/07 07:56 |
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