# Improved statistical machine translation using monolingual paraphrases

arXiv: https://arxiv.org/abs/2109.15119 · HTML: https://mlsanity.com/paper/2109.15119/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 27 references that are in the map.
- First posted on arXiv 25 Sep 2021.

## Built on by (most cited first, 1 of 1)

- [Translating from Morphologically Complex Languages: A Paraphrase-Based Approach](https://mlsanity.com/paper/2109.13724/) (2021)

## Abstract (arXiv)

We propose a novel monolingual sentence paraphrasing method for augmenting the training data for statistical machine translation systems "for free" -- by creating it from data that is already available rather than having to create more aligned data. Starting with a syntactic tree, we recursively generate new sentence variants where noun compounds are paraphrased using suitable prepositions, and vice-versa -- preposition-containing noun phrases are turned into noun compounds. The evaluation shows an improvement equivalent to 33%-50% of that of doubling the amount of training data.