OCR17: Ground Truth and Models for 17th c. French Prints (and hopefully more)

Abstract

Machine learning begins with machine teaching: in the following paper, we present the data that we have prepared to kick-start the training of reliable OCR models for 17th century prints written in French. The construction of a representative corpus is a major challenge: we need to gather documents from different decades and of different genres to cover as many sizes, weights and styles as possible. Historical prints containing glyphs and typefaces that have now disappeared, transcription is a complex act, for which we present guidelines. Finally, we provide preliminary results based on these training data and experiments to improve them.

Keywords

• ocr
• 17th c french
• training data
• corpus building
• data paper
• ocr
• xviième siècle
• données
• construction de corpus
• [shs]humanities and social sciences
• [info]computer science [cs]
• [info.info-ne]computer science [cs]/neural and evolutionary computing [cs.ne]
• [shs.hist]humanities and social sciences/history
• [shs.info]humanities and social sciences/library and information sciences
• [shs.litt]humanities and social sciences/literature