Paraphrasing for Style

What it is about

The paper asks whether a paraphrase system can be steered toward a writing style. Its testbed is Shakespeare's plays paired with their modern prose translations, aligned into roughly 21,000 sentence pairs from one source and about 10,000 from another. A phrase-based statistical MT system is trained in the modern-to-Shakespearean direction and compared with a dictionary-substitution baseline and with paraphrase tables built from out-of-domain text. The authors also ask how well the automatic metrics measure style: BLEU and PINC are joined by three new style scores (cosine similarity, a language model, and logistic regression) that are checked against human judgments. The parallel-trained systems beat both baselines. BLEU tends to mix meaning with style, while the new style scores agree better with people.

Ideas

• I1. Use the dictionary-substitution baseline as the first control for any author delta. The paper's phrase table of about 68,000 word pairs is a count-based substitution. Before claiming that a delta helps, measure the substitution-only output on the same author pairs and report both.
• I2. Add a style score beside chrF in the translator's normal mode. A naive Bayes or logistic model over word and bigram counts, trained on the target author against the standard, says how much of the output sounds like the target. The count tables are kept in BTreeMap order, so the score is deterministic.
• I3. Build a per-author n-gram model as a language-model style score. Perplexity of the output under the target author's model should fall when the delta is applied. The paper's correlation with humans is for one style and small data, so check it on held-out Bible verses first.

For Mova

The code is tools/translate (profile.rs, measure.rs). The paper's phrase-based SMT is not for Mova, but its two-baseline design (substitution and out-of-domain text) is the right control for open problem 6, where the standard leans toward the Bibles. The style scores are the measure to add in normal mode, since exact match alone says nothing about style.

Topics: Machine translation

Cite

The paper itself, not this card. BibTeX from the library's record of the work.

@inproceedings{xu2012paraphrasing,
  title = {{Paraphrasing for Style}},
  author = {Xu, Wei and Ritter, Alan and Dolan, Bill and Grishman, Ralph and Cherry, Colin},
  booktitle = {Proceedings of COLING 2012},
  year = {2012},
  url = {https://aclanthology.org/C12-1177/}
}

References

29 references, 5 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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