Spanish TrOCR：利用迁移学习进行语言适配
Spanish TrOCR: Leveraging Transfer Learning for Language Adaptation
AI总结：
本研究探索TrOCR架构的西班牙语迁移学习，提出资源高效的多语言OCR数据集构建流水线，对比两种适配方法，证明微调方案效果更优，推出当前最优的开源西班牙语OCR模型并公开相关资源。
摘要：
本研究探索了TrOCR架构面向西班牙语的迁移学习能力。TrOCR是一种基于Transformer的光学字符识别（OCR）模型，以其在英文基准测试中的顶尖性能著称。受Li等人关于该模型可适配多语言文本识别的论断启发，我们研究了两种将模型适配到新语言的不同方法：将英文TrOCR编码器与语言特定解码器集成，并在该特定语言上训练模型；以及在新语言数据上微调英文基础TrOCR模型。\n鉴于公开可用数据集的稀缺性，我们提出了一种资源高效的流水线，可用于创建任意语言的OCR数据集，同时针对视觉富文档（VRDs），对所采用的不同图像生成方法进行了全面的基准测试。此外，我们针对西班牙语对这两种方法开展了对比分析，结果表明，在数据集规模固定的情况下，在西班牙语数据上微调英文TrOCR比采用语言特定解码器能获得更优的识别效果。我们在一个公开的印刷体数据集上，采用字符错误率和词错误率指标评估我们的模型，并将其性能与其他开源和云端的西班牙语OCR模型进行对比。据我们所知，这些资源构成了目前最优的西班牙语OCR开源模型。Spanish TrOCR模型已在HuggingFace[20]上公开，生成数据集的代码可在Github[25]上获取。
英文摘要：
This study explores the transfer learning capabilities of the TrOCR architecture to Spanish. TrOCR is a transformer-based Optical Character Recognition (OCR) model renowned for its state-of-the-art performance in English benchmarks. Inspired by Li et al. assertion regarding its adaptability to multilingual text recognition, we investigate two distinct approaches to adapt the model to a new language: integrating an English TrOCR encoder with a language specific decoder and train the model on this specific language, and fine-tuning the English base TrOCR model on a new language data. Due to the scarcity of publicly available datasets, we present a resource-efficient pipeline for creating OCR datasets in any language, along with a comprehensive benchmark of the different image generation methods employed with a focus on Visual Rich Documents (VRDs). Additionally, we offer a comparative analysis of the two approaches for the Spanish language, demonstrating that fine-tuning the English TrOCR on Spanish yields superior recognition than the language specific decoder for a fixed dataset size. We evaluate our model employing character and word error rate metrics on a public available printed dataset, comparing the performance against other open-source and cloud OCR spanish models. As far as we know, these resources represent the best open-source model for OCR in Spanish. The Spanish TrOCR models are publicly available on HuggingFace [20] and the code to generate the dataset is available on Github [25].
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。
