Abstractive Summary Generation for the Urdu Language

• URL: http://arxiv.org/abs/2305.16195v1
• Date: Thu, 25 May 2023 15:55:42 GMT
• Title: Abstractive Summary Generation for the Urdu Language
• Authors: Ali Raza, Hadia Sultan Raja, Usman Maratib
• Abstract summary: We employ a transformer-based model that utilizes self-attention mechanisms to encode the input text and generate a summary. Our experiments show that our model can produce summaries that are grammatically correct and semantically meaningful.
• Score: 1.9594639581421422
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Abstractive summary generation is a challenging task that requires the model to comprehend the source text and generate a concise and coherent summary that captures the essential information. In this paper, we explore the use of an encoder/decoder approach for abstractive summary generation in the Urdu language. We employ a transformer-based model that utilizes self-attention mechanisms to encode the input text and generate a summary. Our experiments show that our model can produce summaries that are grammatically correct and semantically meaningful. We evaluate our model on a publicly available dataset and achieve state-of-the-art results in terms of Rouge scores. We also conduct a qualitative analysis of our model's output to assess its effectiveness and limitations. Our findings suggest that the encoder/decoder approach is a promising method for abstractive summary generation in Urdu and can be extended to other languages with suitable modifications.

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