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Japanese Rhyme Generation Based on Mora Similarity and Generation Probability

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Ryota Mibayashi
Takehiro Yamamoto
Hiroaki Ohshima
Published in
Information Integration and Web Intelligence
Publisher
Springer Nature Switzerland

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Abstract

This chapter introduces a groundbreaking method for generating Japanese rhymes using a language model that considers mora similarity and generation probability. The authors address the challenges of rhyme generation in Japanese, which has fewer vowels and a rhythm based on morae, smaller than syllables. The proposed method uses a pretrained Japanese GPT-2 model and modifies its decoding process to generate rhymes that follow the target mora sequences. The text compares this approach with existing rhyme search services, highlighting the limitations of predefined word lists and strict vowel-level matching. The evaluation results demonstrate that the proposed method outperforms other methods in terms of mora-level similarity and character error rate. The chapter also discusses the potential of generative models for rhyme search and the need for further refinement to address issues such as syntactic incoherence and reading errors. Professionals will gain insights into the innovative use of language models for creative support tools and the potential applications of this method in various fields.
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previous chapter Generating Interactive Japanese Puns Based on Phoneme Similarity
next chapter Addressing Label Scarcity: Hybrid Anomaly Detection in Mental Healthcare Billing
Title
Japanese Rhyme Generation Based on Mora Similarity and Generation Probability
Authors
Ryota Mibayashi
Takehiro Yamamoto
Hiroaki Ohshima
Copyright Year
2026
Book
Information Integration and Web Intelligence

Print ISBN: 978-3-032-11975-9

Electronic ISBN: 978-3-032-11976-6

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-3-032-11976-6_7
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