• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.29-35
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• 2017

In this paper, we present a 5W1H programming model for IT non-experienced people who are not familiar with computer programming and those who need programming education. Based on this model, we can design a development tool that can be easily programmed by beginners. This development tool is a programming method applying the 5W1H concept and constructs a sentence to satisfy the control condition of 'Who, When, Where, What, and How', which is the sentence element of 5W1H. Therefore, the user can easily develop the target system as if constructing the sentence without learning the programming language of the target system. In this paper, to verify the effectiveness of the 5W1H programming model proposed in this paper, we applied the concept of 5W1H programming to Arduino and developed the development tool and performed the first verification and applied the second verification to the speech recognition smart home development platform.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.