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<p>The theater of the Spanish Early Modern period encompasses thousands of textual works and hundreds of playwrights and is one of the greatest examples of Spanish literature. These works were usually copied and altered, changing sometimes the meaning of the original works written by the authors. Therefore, identifying autograph testimonies written directly by the playwrights themselves are of particular importance. In this paper, we address an approach for writer identification based on <i>Deep Convolutional-Recurrent Neural Networks</i> and <i>n</i>-gram language models. The identification task is posed as a classification problem, introducing a probabilistic framework that goes beyond the plain transcription of handwritten text. Experiments are conducted to validate our proposal to distinguish between <i>Lope de Vega</i>’s manuscripts and other <i>non-Lope</i> hands. The good results achieved will ultimately allow to provide modern researchers with a useful tool for cultural heritage recovery.</p>

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Simple handwritten text recognition techniques for highly accurate writer identification

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月15日

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  • Alejandro H. Toselli,
  • Álvaro Cuéllar,
  • Sònia Boadas,
  • Enrique Vidal,
  • Joan Andreu Sánchez

摘要

The theater of the Spanish Early Modern period encompasses thousands of textual works and hundreds of playwrights and is one of the greatest examples of Spanish literature. These works were usually copied and altered, changing sometimes the meaning of the original works written by the authors. Therefore, identifying autograph testimonies written directly by the playwrights themselves are of particular importance. In this paper, we address an approach for writer identification based on Deep Convolutional-Recurrent Neural Networks and n-gram language models. The identification task is posed as a classification problem, introducing a probabilistic framework that goes beyond the plain transcription of handwritten text. Experiments are conducted to validate our proposal to distinguish between Lope de Vega’s manuscripts and other non-Lope hands. The good results achieved will ultimately allow to provide modern researchers with a useful tool for cultural heritage recovery.