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supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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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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