User-Centred Design Actions for Lightweight Evaluation of an Interactive Machine Learning Toolkit
User-Centred Design Actions for Lightweight Evaluation of an Interactive Machine Learning Toolkit
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DOI：
10.7559/citarj.v10i2.509
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发表时间：
2018-01-01
影响因子：
0.2
通讯作者：
Fiebrink, Rebecca
中科院分区：
文献类型：
--
作者：
Bernardo, Francisco;Grierson, Mick;Fiebrink, Rebecca
机器学习为创意产业的开发人员和最终用户提供了巨大的潜力。例如，它可以支持新的基于传感器的交互、程序化内容生成和最终用户产品定制。然而，设计机器学习工具包供创意开发人员采用仍然是一项新生的努力。这项工作的重点是以用户为中心的设计与创造性的最终用户开发人员的应用，为交互式机器学习工具包的设计提供信息。我们介绍了一个框架，以用户为中心的设计行动，我们开发的背景下，欧盟的创新项目，快速混合。我们说明了应用程序的框架与轻量级的形成性评估我们的工具包的JUCE机器学习黑客和快速混合API研讨会在eNTERFACE'17的两个行动。我们描述了我们如何使用这些行动来发现概念和技术上的限制。我们还讨论了这些行动如何使我们更好地了解用户，帮助我们细化设计空间的范围，并对工具包进行了知情的改进。最后，我们的反思，我们从应用以用户为中心的设计创意技术，在创意产业的创新项目的背景下获得的知识。
Machine learning offers great potential to developers and end users in the creative industries. For example, it can support new sensor-based interactions, procedural content generation and end-user product customisation. However, designing machine learning toolkits for adoption by creative developers is still a nascent effort. This work focuses on the application of user-centred design with creative end-user developers for informing the design of an interactive machine learning toolkit. We introduce a framework for user-centred design actions that we developed within the context of an European Union innovation project, RAPID-MIX. We illustrate the application of the framework with two actions for lightweight formative evaluation of our toolkit-the JUCE Machine Learning Hackathon and the RAPID-MIX API workshop at eNTERFACE'17. We describe how we used these actions to uncover conceptual and technical limitations. We also discuss how these actions provided us with a better understanding of users, helped us to refine the scope of the design space, and informed improvements to the toolkit. We conclude with a reflection about the knowledge we obtained from applying user-centred design to creative technology, in the context of an innovation project in the creative industries.