Edit Distances and Their Applications to Downstream Tasks in Research and Commercial Contexts

Félix do Carmo, Diptesh Kanojia
10/8/2024
cs.CL

No official code found. Best implementation: surrey-nlp/AMTA-EditDistances-tutorial (0 stars, last commit 2024-09-20).

Abstract

The tutorial describes the concept of edit distances applied to research and commercial contexts. We use Translation Edit Rate (TER), Levenshtein, Damerau-Levenshtein, Longest Common Subsequence and $n$-gram distances to demonstrate the frailty of statistical metrics when comparing text sequences. Our discussion disassembles them into their essential components. We discuss the centrality of four editing actions: insert, delete, replace and move words, and show their implementations in openly available packages and toolkits. The application of edit distances in downstream tasks often assumes that these accurately represent work done by post-editors and real errors that need to be corrected in MT output. We discuss how imperfect edit distances are in capturing the details of this error correction work and the implications for researchers and for commercial applications, of these uses of edit distances. In terms of commercial applications, we discuss their integration in computer-assisted translation tools and how the perception of the connection between edit distances and post-editor effort affects the definition of translator rates.

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Code Implementations(1)

This repository contains the code and resources for our tutorial presented at AMTA 2024.

01Python, Jupyter NotebookSep 19, 20242 years ago

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Cite this paper

@article{carmo2024edit,
  title  = {Edit Distances and Their Applications to Downstream Tasks in Research and Commercial Contexts},
  author = {Félix do Carmo and Diptesh Kanojia},
  year   = {2024},
  eprint = {2410.05881},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2410.05881v1}
}

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