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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.04878 |
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| _version_ | 1866909677403504640 |
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| author | Torterolo-Orta, Yanco Amor Macicior-Mitxelena, Jaione Miguez-Lamanuzzi, Marina García-Serrano, Ana |
| author_facet | Torterolo-Orta, Yanco Amor Macicior-Mitxelena, Jaione Miguez-Lamanuzzi, Marina García-Serrano, Ana |
| contents | This article presents the experiments and results obtained by the GRESEL team in the IberLEF 2025 shared task PastReader: Transcribing Texts from the Past. Three types of experiments were conducted with the dual aim of participating in the task and enabling comparisons across different approaches. These included the use of a web-based OCR service, a traditional OCR engine, and a compact multimodal model. All experiments were run on consumer-grade hardware, which, despite lacking high-performance computing capacity, provided sufficient storage and stability. The results, while satisfactory, leave room for further improvement. Future work will focus on exploring new techniques and ideas using the Spanish-language dataset provided by the shared task, in collaboration with Biblioteca Nacional de España (BNE). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04878 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Transcribing Spanish Texts from the Past: Experiments with Transkribus, Tesseract and Granite Torterolo-Orta, Yanco Amor Macicior-Mitxelena, Jaione Miguez-Lamanuzzi, Marina García-Serrano, Ana Computer Vision and Pattern Recognition Computation and Language This article presents the experiments and results obtained by the GRESEL team in the IberLEF 2025 shared task PastReader: Transcribing Texts from the Past. Three types of experiments were conducted with the dual aim of participating in the task and enabling comparisons across different approaches. These included the use of a web-based OCR service, a traditional OCR engine, and a compact multimodal model. All experiments were run on consumer-grade hardware, which, despite lacking high-performance computing capacity, provided sufficient storage and stability. The results, while satisfactory, leave room for further improvement. Future work will focus on exploring new techniques and ideas using the Spanish-language dataset provided by the shared task, in collaboration with Biblioteca Nacional de España (BNE). |
| title | Transcribing Spanish Texts from the Past: Experiments with Transkribus, Tesseract and Granite |
| topic | Computer Vision and Pattern Recognition Computation and Language |
| url | https://arxiv.org/abs/2507.04878 |