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基于对话界面的AIGC辅助生成工艺.pdf
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基于对话界面的AIGC辅助生成工艺.pdf
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Highlights in Science, Engineering and Technology
AIDML 2023
Volume 57 (2023)
242
AIGC Assisted Generation Craft Based on Dialogue Interface
Yani Wang
*
and Yuqiang Dong
College of Art and Design, Beijing Forestry University, Beijing, China
Abstract. Design requires a new model to help creators continuously generate, iterate, and evaluate
ideas, i.e. process reengineering based on the raw materials of generated content, as AIGC
becomes increasingly involved in the creative generation of digital content. This paper derives the
human-machine collaborative process of AIGC assisted generation based on dialogue interface from
the entire process of creating the prototype of usable dialogue interface generated by AIGC and
creates a global reference for AI-assisted tool interface design based on particularity.
Keywords: Dialogue interface, AIGC, interface interaction, man-machine collaboration.
1. Introduction
The creation of content, particularly creative labor, has traditionally been regarded as a distinctive
representation of the design perspective. The fresh approach to content development known as AIGC
fosters improved innovation and teamwork in the field of art design while releasing value through
human-machine collaboration. Therefore, from the standpoint of man-machine collaboration, the
design process for AIGC-assisted design can better match user objectives while using resources more
efficiently, expanding design concepts, and assisting designers in improving design efficiency and
quality.
2. Background And Significance Of The Research
2.1. Design-related status of AIGC-assisted content generation
As a tool as well as a method for finding creative answers to issues, art design is typically seen as
the subjective expression of the whole range of the designer's own perspective and imagination. In
2022, AIGC (AI-Generated Content) started to take an increasingly active role in the creative creation
of digital content, including text, photos, audio, and other content or multiple media types of phase
conversion, known as "multimodal content". [1]
With the introduction of the wave of artificial intelligence, the previous emphasis on design
components, manufacturing, and learning may shift to the development of a new order, that is, the
study of people's behavior, emotional changes, and other more complicated processes. [2] In this
situation, design needs new models to assist creators in continuing to conceive, iterate, and evaluate
ideas. This will lead to more efficient, and cost-effective ways of producing digital content. More
accurate and enlightening material is produced by AIGC, as it can learn from vast volumes of data
and spot patterns that humans would not notice. This ability to generate content enables it to produce
a significant amount of content at a low cost and high quality, far exceeding human efficiency. It also
releases value in a collaborative way between humans and machines, allowing content creators and
more common users to redesign and re-create beyond the boundaries of "technique" and "efficiency."
2.2. Man-machine collaborative design process
The term "craft" describes the procedure and method that craftsmen use to treat diverse raw
materials and semi-finished goods before turning them into finished goods. On the one hand, the
content produced by AIGC at the moment is still insufficient to create autonomous design works, and
at its current state, it can only be examined and reasoned in accordance with rules and databases,
which cannot achieve true content understanding but do supply raw materials for design. However,
when designers produce, they tend to base their decisions on their own personal experience, feelings,
and knowledge of aesthetics and user demands, which is process redesigning based on generated
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