Abstract
Handwritten Text Recognition (HTR) is a well-established research area. In contrast, Handwritten Text Generation (HTG) is an emerging field with significant potential. This task is challenging due to the variation in individual handwriting styles. A large and diverse dataset is required to generate realistic handwritten text. However, such datasets are difficult to collect and are not readily available. Bengali is the fifth most spoken language in the world. While several studies exist for languages such as English and Arabic, Bengali handwritten text generation has received little attention. To address this gap, we propose a method for generating Bengali handwritten words. We developed and used a self-collected dataset of Bengali handwriting samples. The dataset includes contributions from approximately five hundred individuals across different ages and genders. All images were pre-processed to ensure consistency and quality. Our approach demonstrates the ability to produce diverse handwritten outputs from input plain text. We believe this work contributes to the advancement of Bengali handwriting generation and can support further research in this area.
Abstract (translated)
手写文本识别（HTR）是一个研究领域，已经相当成熟。相比之下，手写文本生成（HTG）则是一个新兴的、具有巨大潜力的研究方向。然而，由于个体书写风格的变化莫测，这一任务面临诸多挑战。为了生成逼真的手写文本，需要一个大型且多样化的数据集，但这类数据集难以收集并无法轻易获取。 孟加拉语是世界上使用人数第五多的语言。尽管对于英语和阿拉伯语等语言已有若干研究，但对于孟加拉语的手写文本生成却鲜有关注。为填补这一空白，我们提出了一种用于生成孟加拉语手写单词的方法。为此，我们开发并利用了一个由大约500人提供样本的自收集数据集，参与者来自不同的年龄段和性别群体。所有图像都经过预处理以确保一致性和质量。 我们的方法展示了将输入的纯文本转换为多样化的手写输出的能力。我们认为这项工作有助于推进孟加拉语的手写生成技术，并能够支持该领域进一步的研究。
URL
https://arxiv.org/abs/2512.21694
