Toward Fluent Arabic Poem Generation Based on Fine-tuning AraGPT2 Transformer
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-07692-1.pdf
Reference25 articles.
1. Shaalan, K.; Siddiqui, S.; Alkhatib, M.; Abdel Monem, A.: Challenges in arabic natural language processing. Comput. Linguist. Speech Image Process Arabic Lang. (2018). https://doi.org/10.1142/9789813229396_0003
2. Hakami, A.; Alqarni, R.; Almutairi, M.; Alhothali, A.: Arabic Poems Generation using LSTM, Markov-LSTM and pre-trained GPT-2 models. Comput. Sci. Inf. Technol. (2021). https://doi.org/10.5121/csit.2021.111512
3. Al-shaibani, M.S.; Alyafeai, Z.; Ahmad, I.: Meter classification of Arabic poems using deep bidirectional recurrent neural networks. Pattern Recognit. Lett. (2020). https://doi.org/10.1016/j.patrec.2020.05.028
4. Al-Talabani, A.K.: “Automatic recognition of arabic poetry meter from speech signal using long short-term memory and support vector machine. ARO-Sci. J. Koya Univ. (2020). https://doi.org/10.14500/aro.10631
5. Talafha, S.; Rekabdar, B.: Arabic poem generation incorporating deep learning and phonetic CNNsubword embedding models. Int. J. Robot. Comput. (2019). https://doi.org/10.35708/tai1868-126246
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