Abstract
Monodic folk music has traditionally been preserved in physical documents. It constitutes a vast archive that needs to be digitized to facilitate comprehensive analysis using AI techniques. A critical component of music score digitization is the transcription of lyrics, an extensively researched process in Optical Character Recognition (OCR) and document layout analysis. These fields typically require the development of specific models that operate in several stages: first, to detect the bounding boxes of specific texts, then to identify the language, and finally, to recognize the characters. Recent advances in vision language models (VLMs) have introduced multimodal capabilities, such as processing images and text, which are competitive with traditional OCR methods. This paper proposes an end-to-end system for extracting lyrics from images of handwritten musical scores. We aim to evaluate the performance of two state-of-the-art VLMs to determine whether they can eliminate the need to develop specialized text recognition and OCR models for this task. The results of the study, obtained from a dataset in a real-world application environment, are presented along with promising new research directions in the field. This progress contributes to preserving cultural heritage and opens up new possibilities for global analysis and research in folk music.
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Acknowledgments
We would like to express our gratitude for the assistance from Gilberto Bernardes and Nádia Carvalho from INESC TEC - Institute for Systems and Computer Engineering, Technology and Science in carrying out the case study of this research. Research funded by the project “EA-DIGIFOLK: AN EUROPEAN AND IBERO-AMERICAN APPROACH FOR THE DIGITAL COLLECTION, ANALYSIS AND DISSEMINATION OF FOLK MUSIC” (101086338) under the program Marie Skłodowska-Curie Actions Staff Exchanges (HORIZON-MSCA-2021-SE-01-01).
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Sales Mendes, A., Lozano Murciego, Á., Silva, L.A., Jiménez-Bravo, D.M., Navarro-Cáceres, M., Bernardes, G. (2025). Evaluation of Lyrics Extraction from Folk Music Sheets Using Vision Language Models (VLMs). In: Santos, M.F., Machado, J., Novais, P., Cortez, P., Moreira, P.M. (eds) Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science(), vol 14967. Springer, Cham. https://doi.org/10.1007/978-3-031-73497-7_8
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