  This study explores the integration of advanced Natural Language Processing
(NLP) and Artificial Intelligence (AI) techniques to analyze and interpret
Persian literature, focusing on the poetry of Forough Farrokhzad. Utilizing
computational methods, we aim to unveil thematic, stylistic, and linguistic
patterns in Persian poetry. Specifically, the study employs AI models including
transformer-based language models for clustering of the poems in an
unsupervised framework. This research underscores the potential of AI in
enhancing our understanding of Persian literary heritage, with Forough
Farrokhzad's work providing a comprehensive case study. This approach not only
contributes to the field of Persian Digital Humanities but also sets a
precedent for future research in Persian literary studies using computational
techniques.
