A Machine Learning Approach to Evaluating Translation Quality

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This paper explores the possibility of applying Machine Learning for Machine Translation evaluation.

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2 p.

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Reyes Ayala, Brenda & Chen, Jiangping June 20, 2017.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Information to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 43 times . More information about this paper can be viewed below.

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This paper explores the possibility of applying Machine Learning for Machine Translation evaluation.

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2 p.

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Abstract: We explored supervised machine learning (ML) techniques to understand and predict the adequacy and fluency of English-Spanish machine translation. Five experiments were conducted using three classifiers in Weka, an open-source ML tool.We found that the highest performance was achieved by applying a dimensionality reduction approach to the classification task, which included collapsing a numeric scale of quality to two categories: high quality and low quality. Our results showed that the Support Vector Machine classifier performed the best at predicting the adequacy (65.65%) and fluency (65.77%) of the translations. More research is needed to explore the methodologies of applying ML to translation evaluation.

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  • ACM/IEEE-CS Joint Conference on Digital Libraries, June 19-23, 2017. Toronto, Canada.

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  • Publication Title: Proceedings of the 2017 ACM/IEEE-CS Joint Conference on Digital Libraries
  • Peer Reviewed: Yes

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UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

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A Machine Learning Approach to Evaluating Translation Quality (Poster)

A Machine Learning Approach to Evaluating Translation Quality

Poster presented at the 2017 ACM/IEEE-CS Joint Conference on Digital Libraries. explores the possibility of applying Machine Learning for Machine Translation evaluation.

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[Poster] "A Machine Learning Approach to Evaluating Translation Quality," ark:/67531/metadc990997

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  • June 20, 2017

Added to The UNT Digital Library

  • Sept. 17, 2017, 6:24 p.m.

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Reyes Ayala, Brenda & Chen, Jiangping. A Machine Learning Approach to Evaluating Translation Quality, paper, June 20, 2017; (digital.library.unt.edu/ark:/67531/metadc993374/: accessed August 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Information.