AI RESEARCH
Mind Your Moras: Orthography-Aware Error Analysis of Neural Japanese Morphological Generation
arXiv CS.CL
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ArXi:2605.20043v1 Announce Type: new We present an orthography-aware error analysis of Japanese past-tense morphological inflection, treating hiragana not merely as a transcriptional medium, but as a representational system encoding morphophonological distinctions that may influence model generalization. We evaluate two character-level sequence-to-sequence architectures on past-tense formation using datasets formatted according to the SIGMORPHON 2020 and 2023 shared task conventions.