@inproceedings{wieler-etal-2026-hannoi,
title = "{HA}nno{I}: A Handwriting Annotation Interface to Extract Data for Linguistic Analyses of Graphetic Detail",
author = "Wieler, Joshua and
Petitjean, Simon and
Berg, Kristian and
Huber, Henriette and
Hartmann, Stefan",
editor = "Gorman, Kyle",
booktitle = "Proceedings of the Third Workshop on Computation and Written Language ({CAWL} 2026) @ {LREC} 2026",
month = jun,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.cawl-1.3/",
doi = "10.63317/2i7h8bznd292",
pages = "33--44",
abstract = "In this paper, we present HAnnoI {--} short for Handwriting Annotation Interface {--}, an open-source GUI application developed in Python that allows its users to identify and annotate so-called Regions of Interest (ROIs) within digital images. Several meta data such as their coordinates are retained for each ROI and they can be annotated on user-defined annotation layers. HAnnoI comes with a function to export all annotations to a CSV file, enabling further processing as well as quantitative analyses. HAnnoI also has a function to extract single PNG image files of all ROIs. It was developed to mark and annotate single letters in scans of handwritten (alphabetic) texts for linguistic analyses, yet it is not limited to this particular use case. In this paper, we first provide information on HAnnoI{'}s conception and technical details as well as an overview of alternative applications. We then showcase HAnnoI{'}s capabilities in a letter annotation task, where five annotators marked instances of lower case {\ensuremath{<}}s{\ensuremath{>}} in handwritten texts. Finally, we report on an exploratory analysis of this data, showing what kinds of investigations are enabled by using HAnnoI. The tool is available for free use at \url{https://github.com/pywielR/HAnnoI}."
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<abstract>In this paper, we present HAnnoI – short for Handwriting Annotation Interface –, an open-source GUI application developed in Python that allows its users to identify and annotate so-called Regions of Interest (ROIs) within digital images. Several meta data such as their coordinates are retained for each ROI and they can be annotated on user-defined annotation layers. HAnnoI comes with a function to export all annotations to a CSV file, enabling further processing as well as quantitative analyses. HAnnoI also has a function to extract single PNG image files of all ROIs. It was developed to mark and annotate single letters in scans of handwritten (alphabetic) texts for linguistic analyses, yet it is not limited to this particular use case. In this paper, we first provide information on HAnnoI’s conception and technical details as well as an overview of alternative applications. We then showcase HAnnoI’s capabilities in a letter annotation task, where five annotators marked instances of lower case \ensuremath<s\ensuremath> in handwritten texts. Finally, we report on an exploratory analysis of this data, showing what kinds of investigations are enabled by using HAnnoI. The tool is available for free use at https://github.com/pywielR/HAnnoI.</abstract>
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%0 Conference Proceedings
%T HAnnoI: A Handwriting Annotation Interface to Extract Data for Linguistic Analyses of Graphetic Detail
%A Wieler, Joshua
%A Petitjean, Simon
%A Berg, Kristian
%A Huber, Henriette
%A Hartmann, Stefan
%Y Gorman, Kyle
%S Proceedings of the Third Workshop on Computation and Written Language (CAWL 2026) @ LREC 2026
%D 2026
%8 June
%I ELRA Language Resources Association (ELRA)
%C Palma de Mallorca, Spain
%F wieler-etal-2026-hannoi
%X In this paper, we present HAnnoI – short for Handwriting Annotation Interface –, an open-source GUI application developed in Python that allows its users to identify and annotate so-called Regions of Interest (ROIs) within digital images. Several meta data such as their coordinates are retained for each ROI and they can be annotated on user-defined annotation layers. HAnnoI comes with a function to export all annotations to a CSV file, enabling further processing as well as quantitative analyses. HAnnoI also has a function to extract single PNG image files of all ROIs. It was developed to mark and annotate single letters in scans of handwritten (alphabetic) texts for linguistic analyses, yet it is not limited to this particular use case. In this paper, we first provide information on HAnnoI’s conception and technical details as well as an overview of alternative applications. We then showcase HAnnoI’s capabilities in a letter annotation task, where five annotators marked instances of lower case \ensuremath<s\ensuremath> in handwritten texts. Finally, we report on an exploratory analysis of this data, showing what kinds of investigations are enabled by using HAnnoI. The tool is available for free use at https://github.com/pywielR/HAnnoI.
%R 10.63317/2i7h8bznd292
%U https://aclanthology.org/2026.cawl-1.3/
%U https://doi.org/10.63317/2i7h8bznd292
%P 33-44
Markdown (Informal)
[HAnnoI: A Handwriting Annotation Interface to Extract Data for Linguistic Analyses of Graphetic Detail](https://aclanthology.org/2026.cawl-1.3/) (Wieler et al., CAWL 2026)
ACL