Abstract
In this project, we develop a practical and efficient solution for automating the Manhwa translation from Indonesian to English. Our approach combines computer vision, text recognition, and natural language processing techniques to streamline the traditionally manual process of Manhwa(Korean comics) translation. The pipeline includes fine-tuned YOLOv5xu for speech bubble detection, Tesseract for OCR and fine-tuned MarianMT for machine translation. By automating these steps, we aim to make Manhwa more accessible to a global audience while saving time and effort compared to manual translation methods. While most Manhwa translation efforts focus on Japanese-to-English, we focus on Indonesian-to-English translation to address the challenges of working with low-resource languages. Our model shows good results at each step and was able to translate from Indonesian to English efficiently.
Abstract (translated)
在这个项目中，我们开发了一种实用且高效的解决方案，用于自动化从印尼语到英语的漫画（又称Manhwa，即韩式漫画）翻译过程。我们的方法结合了计算机视觉、文本识别和自然语言处理技术，以简化传统手动翻译Manhwa的过程。该流程包括使用经过微调的YOLOv5xu进行气泡检测、Tesseract进行OCR文字识别以及经过微调的MarianMT用于机器翻译。通过自动化这些步骤，我们旨在使更多的Manhwa作品能够被全球观众接触和理解，并且相比手动翻译方法可以节省大量时间和精力。 大多数Manhwa翻译工作主要集中在日语到英语的翻译上，而我们的项目则专注于印尼语到英语的翻译，以解决处理低资源语言所面临的挑战。我们的模型在每个步骤中都显示出良好的效果，并能够高效地完成从印尼语到英语的翻译任务。
URL
https://arxiv.org/abs/2501.01629
