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Findings of the First WMT Shared Task on Sign Language Translation

This repository contains data and scripts for reproducing the evaluation of the WMT22 Sign Language Translation Task.

Human evaluation

The files related to the human evaluation reside in the directory human_evaluation.

Scripts:

  • generate-batches.sh - produces batches for Appraise
  • generate-snippets.sh - splits documents into 10-segment long chunks
  • generate-ranking.sh - computes ranking from scores exported from Appraise
  • scripts/iaa.py - for generating intra-annotator agreements
  • scripts/create_histogram.py - for generating the histogram that appears in the paper

Data:

  • slttest2022.dsgs-de.all.xml - the official test set
  • submissions/*.xml - the official submissions to the shared task
  • submissions/slttest22-doc-snippets.tsv - document chunks
  • batches/*.json - JSON batches for creating a campaign in Appraise
  • scores/*.csv - scores exported from Appraise
  • ranking.log - output of Appraise script for computing system rankings

Automatic evaluation

The files related to the human evaluation reside in the directory automatic_evaluation.

Scripts (directory tools):

  • automaticEval.py - Automatic evaluation with BLEU, chrF++ and BLEURT for WMT-SLT 2022 Confidence intervals obtained via bootstrap resampling
  • corrMetricsHuman.py - Pearson and Spearman correlations for the automatic metrics
  • plotMetrics.py - 3D plot of the correlation between the automatic metrics

Requirements

For running most scripts one needs to create a Python virtual enviroment and install

virtualenv venv
source venv/bin/activate
pip install -r requirements.txt

*(The BLEURT requirements include Tensorflow which a heavy thing to download. If you don't need that, feel free to comment out the BLEURT requirement entry to save time and hard disk space).

As an exception, the script generate-batches.sh requires one to install Appraise from this repository:

git clone https://github.com/AppraiseDev/Appraise.git
cd Appraise
git checkout 147865c284d340085d1333e1b7ed2a40d52bd703

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Evaluation of the first shared task for machine translation of sign language

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