Handwritten Text Recognition (HTR) technology is now a mature machine learning tool, becoming integrated in the digitisation processes of libraries and archives, speeding up the transcription of primary sources and facilitating full text searching and analysis of historic texts at scale. However, research into how HTR is changing our information environment is scant. This paper presents a systematic literature review regarding how researchers are using one particular HTR platform, Transkribus, to indicate the domains where HTR is applied, the approach taken, and how the technology is understood. 381 papers from 2015 to 2020 were gathered from Google Scholar, Scopus, and Web of Science, then grouped and coded into categories using quantitative and qualitative approaches. Published research that mentions Transkribus is international and rapidly growing. Transkribus features primarily in archival and library science publications, while a long tail of broad and eclectic disciplines, including history, computer science, citizen science, law and education, demonstrate the wider applicability of the tool. The most common paper categories were humanities applications (67%), technological (25%), users (5%) and tutorials (3%). This paper presents the first overarching review of HTR as featured in published research, while also elucidating how HTR is affecting the information environment.

手写文本识别（HTR）技术现已成为一种成熟的机器学习工具，已集成到图书馆和档案馆的数字化过程中，加快了主要来源的转录速度，并促进了大规模历史文本的全文搜索和分析。然而，关于 HTR 如何改变我们的信息环境的研究还很少。本文对研究人员如何使用特定的 HTR 平台 Transkribus 进行了系统的文献综述，以表明 HTR 的应用领域、采用的方法以及如何理解该技术。从 Google Scholar、Scopus 和 Web of Science 收集了 2015 年至 2020 年的 381 篇论文，然后使用定量和定性方法进行分组和编码。已发表的提到 Transkribus 的研究是国际性的并且正在快速发展。 Transkribus 主要用于档案和图书馆学出版物，而一系列广泛且不拘一格的学科，包括历史、计算机科学、公民科学、法律和教育，证明了该工具更广泛的适用性。最常见的论文类别是人文应用（67%）、技术（25%）、用户（5%）和教程（3%）。本文首次对已发表的研究中的 HTR 进行了总体回顾，同时还阐明了 HTR 如何影响信息环境。