Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for the Quality Assessment of Emotion Translation

Shenbin Qian, Constantin Orasan, Felix do Carmo, Qiuliang Li, Diptesh Kanojia
6/20/2023
cs.CL

No official code found. Best implementation: surrey-nlp/HADQAET (2 stars, last commit 2024-11-17).

Abstract

In this paper, we focus on how current Machine Translation (MT) tools perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a framework proposed in this paper. We propose this evaluation framework based on the Multidimensional Quality Metrics (MQM) and perform a detailed error analysis of the MT outputs. From our analysis, we observe that about 50% of the MT outputs fail to preserve the original emotion. After further analysis of the errors, we find that emotion carrying words and linguistic phenomena such as polysemous words, negation, abbreviation etc., are common causes for these translation errors.

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Code Implementations(1)

surrey-nlp/HADQAETCommunity100%

This repository contains the dataset for our paper "Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for the Quality Assessment of Emotion Translation"

20Apr 13, 20231 years ago
chinese-english-translationemotion-transfertranslation-quality-estimation

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Cite this paper

@article{qian2023evaluation,
  title  = {Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for the Quality Assessment of Emotion Translation},
  author = {Shenbin Qian and Constantin Orasan and Felix do Carmo and Qiuliang Li and Diptesh Kanojia},
  year   = {2023},
  eprint = {2306.11900},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.11900v1}
}

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