May 14, 2024, 4:49 a.m. | Arash Rasti Meymandi, Zahra Hosseini, Sina Davari, Abolfazl Moshiri, Shabnam Rahimi-Golkhandan, Khashayar Namdar, Nikta Feizi, Mohamad Tavakoli-Targhi

cs.CL updates on arXiv.org arxiv.org

arXiv:2405.06760v1 Announce Type: new
Abstract: 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 …

abstract advanced aim analyze artificial artificial intelligence arxiv case case study computational cs.ai cs.cl digital digital humanities humanities integration intelligence language language models language processing literature natural natural language natural language processing nlp opportunities poetry processing research study type

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