Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917662853955584 |
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| author | Meymandi, Arash Rasti Hosseini, Zahra Davari, Sina Moshiri, Abolfazl Rahimi-Golkhandan, Shabnam Namdar, Khashayar Feizi, Nikta Tavakoli-Targhi, Mohamad Khalvati, Farzad |
| author_facet | Meymandi, Arash Rasti Hosseini, Zahra Davari, Sina Moshiri, Abolfazl Rahimi-Golkhandan, Shabnam Namdar, Khashayar Feizi, Nikta Tavakoli-Targhi, Mohamad Khalvati, Farzad |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_06760 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad Meymandi, Arash Rasti Hosseini, Zahra Davari, Sina Moshiri, Abolfazl Rahimi-Golkhandan, Shabnam Namdar, Khashayar Feizi, Nikta Tavakoli-Targhi, Mohamad Khalvati, Farzad Computation and Language Artificial Intelligence 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. |
| title | Opportunities for Persian Digital Humanities Research with Artificial Intelligence Language Models; Case Study: Forough Farrokhzad |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2405.06760 |