Summary of Formality Style Transfer in Persian, by Parastoo Falakaflaki et al.
Formality Style Transfer in Persian
by Parastoo Falakaflaki, Mehrnoush Shamsfard
First submitted to arxiv on: 2 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The study proposes a novel model, Fa-BERT2BERT, for formality style transfer in Persian, addressing challenges posed by informal language on digital platforms. The model incorporates consistency learning and gradient-based dynamic weighting to improve its understanding of syntactic variations. Evaluation against existing methods shows superior performance across various metrics, including BLEU, BERT score, Rouge-l, and proposed metrics. The study contributes to Persian language processing by enhancing the accuracy and functionality of NLP models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper tries to make computers better at changing informal text into formal text while keeping the same meaning. They create a new model that’s good at understanding how sentences are put together and how words are used in different styles. The results show that this new model works better than other methods for changing Persian text from informal to formal. This is important because it can help make computers better at understanding and processing language, which can be useful for things like filtering out bad content online or helping people communicate across languages. |
Keywords
» Artificial intelligence » Bert » Bleu » Nlp » Rouge » Style transfer
