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arXiv 2309.02402cs.HC
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打破创意表达的障碍:共同设计与实现一个无障碍的文本到图像界面

Breaking Barriers to Creative Expression: Co-Designing and Implementing an Accessible Text-to-Image Interface

Atieh Taheri, Mohammad Izadi, Gururaj Shriram, Negar Rostamzadeh, Shaun Kane

AI总结:

本文通过共同设计并实现一个利用大型语言模型提供建议、减少打字负担的无障碍文本到图像界面,旨在降低创意表达的门槛,并验证了其对不同能力用户创作视觉艺术的支持作用。

摘要:

文本到图像生成模型因其能够根据文本提示生成高质量图像而日益流行。该技术的一个用途是使艺术创作软件更加无障碍。在本文中,我们记录了一个替代性用户界面的开发过程,该界面通过提供来自大型语言模型的建议来减少输入图像提示所需的打字工作量,并通过项目团队内的迭代设计和测试进行开发。测试结果表明,生成式文本模型如何支持文本到图像模型的无障碍性,使具有不同能力的用户能够创作视觉艺术。

英文摘要:

Text-to-image generation models have grown in popularity due to their ability to produce high-quality images from a text prompt. One use for this technology is to enable the creation of more accessible art creation software. In this paper, we document the development of an alternative user interface that reduces the typing effort needed to enter image prompts by providing suggestions from a large language model, developed through iterative design and testing within the project team. The results of this testing demonstrate how generative text models can support the accessibility of text-to-image models, enabling users with a range of abilities to create visual art.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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