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        <title>Layout-Based Chunk Alignment: Utilizing Visual Information to Collect Parallel Texts From Image Documents</title>
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        <namePart type="given">Masaki</namePart>
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        <namePart type="given">Kayoko</namePart>
        <namePart type="family">Nohara</namePart>
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    <name type="personal">
        <namePart type="given">Yuma</namePart>
        <namePart type="family">Miura</namePart>
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            <title>Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)</title>
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    <abstract>This study proposes a layout-based chunk alignment method (Layout-CA) as an intermediate step between document- and sentence-level parallel text alignment for bilingual document images. Visually rich printed materials, such as institutional reports and magazines, often contain high-quality translations and are valuable sources of parallel data, yet their layout cues are underutilized. Layout-CA aligns semantically coherent text chunks across document pairs by integrating multi-modal cues from textual content and layout, and sentence alignment is then performed within the aligned chunk pairs. Experiments on English UNESCO reports and their Japanese translations show that introducing chunk alignment improves downstream sentence alignment for both Bleualign and Vecalign. When document order is disrupted, Layout-CA preserves alignment coverage by restricting sentence matching to corresponding chunks, enabling robust alignment in multilingual image documents.</abstract>
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%0 Conference Proceedings
%T Layout-Based Chunk Alignment: Utilizing Visual Information to Collect Parallel Texts From Image Documents
%A Kinouchi, Masaki
%A Nohara, Kayoko
%A Zhu, Xinru
%A Miura, Yuma
%Y Briakou, Eleftheria
%Y Gwinnup, Jeremy
%Y Goel, Shivali
%S Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)
%D 2026
%8 August
%I Association for Machine Translation in the Americas
%C Québec City, Canada
%F kinouchi-etal-2026-layout
%X This study proposes a layout-based chunk alignment method (Layout-CA) as an intermediate step between document- and sentence-level parallel text alignment for bilingual document images. Visually rich printed materials, such as institutional reports and magazines, often contain high-quality translations and are valuable sources of parallel data, yet their layout cues are underutilized. Layout-CA aligns semantically coherent text chunks across document pairs by integrating multi-modal cues from textual content and layout, and sentence alignment is then performed within the aligned chunk pairs. Experiments on English UNESCO reports and their Japanese translations show that introducing chunk alignment improves downstream sentence alignment for both Bleualign and Vecalign. When document order is disrupted, Layout-CA preserves alignment coverage by restricting sentence matching to corresponding chunks, enabling robust alignment in multilingual image documents.
%U https://aclanthology.org/2026.amta-research.8/
%P 135-145

Markdown (Informal)

[Layout-Based Chunk Alignment: Utilizing Visual Information to Collect Parallel Texts From Image Documents](https://aclanthology.org/2026.amta-research.8/) (Kinouchi et al., AMTA 2026)

• Layout-Based Chunk Alignment: Utilizing Visual Information to Collect Parallel Texts From Image Documents (Kinouchi et al., AMTA 2026)

ACL

• Masaki Kinouchi, Kayoko Nohara, Xinru Zhu, and Yuma Miura. 2026. Layout-Based Chunk Alignment: Utilizing Visual Information to Collect Parallel Texts From Image Documents. In Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), pages 135–145, Québec City, Canada. Association for Machine Translation in the Americas.