Feb. 1, 2024, 12:41 p.m. | Christeena Varghese Sergey Koshelev Ivan P. Yamshchikov

cs.CL updates on arXiv.org arxiv.org

This study explores four methods of generating paraphrases in Malayalam, utilizing resources available for English paraphrasing and pre-trained Neural Machine Translation (NMT) models. We evaluate the resulting paraphrases using both automated metrics, such as BLEU, METEOR, and cosine similarity, as well as human annotation. Our findings suggest that automated evaluation measures may not be fully appropriate for Malayalam, as they do not consistently align with human judgment. This discrepancy underscores the need for more nuanced paraphrase evaluation approaches especially for …

annotation automated bleu cs.ai cs.cl english evaluation human machine machine translation meteor metrics neural machine translation paraphrasing resources study translation

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