Kuzushiji transcription using hiragana-level fusion of optical character recognition and read-speech automatic speech recognition
Abstract
This letter proposes a new Kuzushiji transcription framework that integrates optical character recognition (OCR) with read-speech automatic speech recognition (ASR) via hiragana-level fusion, without requiring additional model training. The framework uses the transcriber’s read-speech as an additional modality to guide beam-search OCR hypothesis selection for Kuzushiji transcription. Each OCR candidate is scored based on its phonetic similarity to the ASR output of the corresponding Kuzushiji read-speech at the hiragana-sequence level. Evaluation results show the effectiveness of the proposed framework in reducing the character error rate in contrast to conventional OCR-only Kuzushiji transcription.
Fields of Study & Subjects
Speech Recognition and Synthesis
Handwritten Text Recognition Techniques
Natural Language Processing Techniques
Publication details
- Journal / source
- Nippon Onkyo Gakkaishi/Acoustical science and technology/Nihon Onkyo Gakkaishi
- Publisher
- Acoustical Society of Japan
- Volume
- 47
- Issue
- 4
- Pages
- 358–362
- Publication date
- 6 April 2026
- Language
- EN