# UDAAN: Machine Learning based Post-Editing tool for Document Translation

arXiv: https://arxiv.org/abs/2203.01644 · HTML: https://mlsanity.com/paper/2203.01644/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 33 references that are in the map.
- First posted on arXiv 3 Mar 2022.

## Builds on (most cited first, 12 of 12)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://mlsanity.com/paper/1904.01038/) (2019)
- [Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation](https://mlsanity.com/paper/2104.14478/) (2021)
- [LSTM: A Search Space Odyssey](https://mlsanity.com/paper/1503.04069/) (2015)
- [Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search](https://mlsanity.com/paper/1704.07138/) (2017)
- [SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings](https://mlsanity.com/paper/2004.08728/) (2020)
- [Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages](https://mlsanity.com/paper/2104.05596/) (2021)
- [A Supervised Word Alignment Method based on Cross-Language Span Prediction using Multilingual BERT](https://mlsanity.com/paper/2004.14516/) (2020)
- [On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation](https://mlsanity.com/paper/1809.03985/) (2018)
- [IntelliCAT: Intelligent Machine Translation Post-Editing with Quality Estimation and Translation Suggestion](https://mlsanity.com/paper/2105.12172/) (2021)
- [Learning to Robustly Aggregate Labeling Functions for Semi-supervised Data Programming](https://mlsanity.com/paper/2109.11410/) (2021)
- [SPEAR : Semi-supervised Data Programming in Python](https://mlsanity.com/paper/2108.00373/) (2021)

## Built on by (most cited first, 3 of 3)

- [A Benchmark and Dataset for Post-OCR text correction in Sanskrit](https://mlsanity.com/paper/2211.07980/) (2022)
- [PARAM-1 BharatGen 2.9B Model](https://mlsanity.com/paper/2507.13390/) (2025)
- [DICTDIS: Dictionary Constrained Disambiguation for Improved NMT](https://mlsanity.com/paper/2210.06996/) (2022)

## Abstract (arXiv)

We introduce UDAAN, an open-source post-editing tool that can reduce manual editing efforts to quickly produce publishable-standard documents in several Indic languages. UDAAN has an end-to-end Machine Translation (MT) plus post-editing pipeline wherein users can upload a document to obtain raw MT output. Further, users can edit the raw translations using our tool. UDAAN offers several advantages: a) Domain-aware, vocabulary-based lexical constrained MT. b) source-target and target-target lexicon suggestions for users. Replacements are based on the source and target texts lexicon alignment. c) Translation suggestions are based on logs created during user interaction. d) Source-target sentence alignment visualisation that reduces the cognitive load of users during editing. e) Translated outputs from our tool are available in multiple formats: docs, latex, and PDF. We also provide the facility to use around 100 in-domain dictionaries for lexicon-aware machine translation. Although we limit our experiments to English-to-Hindi translation, our tool is independent of the source and target languages. Experimental results based on the usage of the tools and users feedback show that our tool speeds up the translation time by approximately a factor of three compared to the baseline method of translating documents from scratch. Our tool is available for both Windows and Linux platforms. The tool is open-source under MIT license, and the source code can be accessed from our website at https://www.udaanproject.org. Demonstration and tutorial videos for various features of our tool can be accessed at https://www.youtube.com/channel/UClfK7iC8J7b22bj3GwAUaCw. Our MT pipeline can be accessed at https://udaaniitb.aicte-india.org/udaan/translate/.