An Evaluation of Persian-English Machine Translation Datasets with Transformers

• URL: http://arxiv.org/abs/2302.00321v1
• Date: Wed, 1 Feb 2023 08:55:08 GMT
• Title: An Evaluation of Persian-English Machine Translation Datasets with Transformers
• Authors: Amir Sartipi, Meghdad Dehghan, Afsaneh Fatemi
• Abstract summary: This study collected and analysed the most popular and valuable parallel corpora, which were used for Persian-English translation. We fine-tuned and evaluated two state-of-the-art attention-based seq2seq models on each dataset separately.
• Score: 1.0742675209112622
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Nowadays, many researchers are focusing their attention on the subject of machine translation (MT). However, Persian machine translation has remained unexplored despite a vast amount of research being conducted in languages with high resources, such as English. Moreover, while a substantial amount of research has been undertaken in statistical machine translation for some datasets in Persian, there is currently no standard baseline for transformer-based text2text models on each corpus. This study collected and analysed the most popular and valuable parallel corpora, which were used for Persian-English translation. Furthermore, we fine-tuned and evaluated two state-of-the-art attention-based seq2seq models on each dataset separately (48 results). We hope this paper will assist researchers in comparing their Persian to English and vice versa machine translation results to a standard baseline.

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