Summary of Opportunities For Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad, by Arash Rasti Meymandi et al.
Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad
by Arash Rasti Meymandi, Zahra Hosseini, Sina Davari, Abolfazl Moshiri, Shabnam Rahimi-Golkhandan, Khashayar Namdar, Nikta Feizi, Mohamad Tavakoli-Targhi, Farzad Khalvati
First submitted to arxiv on: 10 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper combines advanced Natural Language Processing (NLP) and Artificial Intelligence (AI) techniques to analyze and interpret Persian literature, focusing on Forough Farrokhzad’s poetry. The study employs transformer-based language models to cluster poems in an unsupervised framework, aiming to uncover thematic, stylistic, and linguistic patterns. The research demonstrates the potential of AI in enhancing our understanding of Persian literary heritage, with Forough Farrokhzad’s work serving as a comprehensive case study. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper uses special computer programs to understand and analyze Persian poetry, specifically focusing on the work of Forough Farrokhzad. It wants to find patterns and connections in the poems that reveal what they’re about and how they were written. The research shows how computers can help us better understand Persian literature and its significance. |
Keywords
» Artificial intelligence » Natural language processing » Nlp » Transformer » Unsupervised
