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diff --git a/docs/index.md b/docs/index.md index ada2601..7ec4361 100644 --- a/docs/index.md +++ b/docs/index.md @@ -3,30 +3,29 @@ The goal of quality estimation (QE) is to evaluate the quality of a translation With TransQuest, we have opensourced our research in translation quality estimation which also won the sentence-level direct assessment quality estimation shared task in [WMT 2020](http://www.statmt.org/wmt20/quality-estimation-task.html). TransQuest outperforms current open-source quality estimation frameworks such as [OpenKiwi](https://github.com/Unbabel/OpenKiwi) and [DeepQuest](https://github.com/sheffieldnlp/deepQuest). - -## Installation -You first need to install PyTorch. The recommended PyTorch version is 1.6. -Please refer to [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform. - -When PyTorch has been installed, you can install TransQuest from source or from pip. - - -### From pip - -```bash -pip install transquest -``` - -### From Source - -```bash -git clone https://github.com/TharinduDR/TransQuest.git -cd TransQuest -pip install -r requirements.txt -``` - -!!! warning -We recommend installing TransQuest with pip since it will be more stable. Also make sure that you are working with the latest version available in pip. +## Features +- Sentence-level translation quality estimation on both aspects: predicting post editing efforts and direct assessment. +- Word-level translation quality estimation capable of predicting quality of source words, target words and target gaps. +- Perform significantly better than current state-of-the-art quality estimation methods like DeepQuest and OpenKiwi in all the languages experimented. +- Pre-trained quality estimation models for fifteen language pairs. + +## Table of Contents +1. [Installation](https://tharindudr.github.io/TransQuest/install/) +Install TransQuest locally using pip. +2. Architectures +Checkout the architectures implemented in TransQuest + 1. [Sentence-level Architectures](https://tharindudr.github.io/TransQuest/sentence_level_architectures/) - We have released two architectures; MonoTransQuest and SiameseTransQuest to perform sentence level quality estimation. + 2. [Word-level Architecture](https://tharindudr.github.io/TransQuest/word_level_architecture/) - We have released MicroTransQuest to perform word level quality estimation. +3. Examples +We have provided several examples on how to use TransQuest in recent WMT quality estimation shared tasks. + 1. [Sentence-level Examples](https://tharindudr.github.io/TransQuest/sentence_level_examples/) + 2. [Word-level Examples](https://tharindudr.github.io/TransQuest/word_level_examples/) +4. Pre-trained Models +We have provided pretrained quality estimation models for fifteen language pairs covering both sentence-level and word-level + 1. [Sentence-level Models](https://tharindudr.github.io/TransQuest/sentence_level_pretrained/) + 2. [Sentence-level Models](https://tharindudr.github.io/TransQuest/sentence_level_pretrained/) +5. [Contact](https://tharindudr.github.io/TransQuest/contact/) +Contact us for any issues with TransQuest ## Resources - [Research Seminar](https://youtu.be/xbsbHUVVF3s) done on 1st of October 2020 in [RGCL](http://rgcl.wlv.ac.uk/2020/09/24/research-seminar/) and the [slides](https://www.slideshare.net/TharinduRanasinghe1/transquest-238713809). |