Machine translation evaluation metrics for quality assessment of automatically simplified sentences

Popović, Maja ; Štajner, Sanja

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Document Type: Conference or workshop publication
Year of publication: 2016
Book title: qats2016 : LREC 2016 Workshop & Shared Task on Quality Assessment for Text Simplification (QATS), 28th May 2016, Portorož, Slovenia ; proceedings
Page range: 32-37
Conference title: Qats2016
Location of the conference venue: Portorož, Slovenia
Date of the conference: 28 May 2016
Publisher: Štajner, Sanja
Place of publication: Paris
Publishing house: ELRA-ERDA
Publication language: English
Institution: School of Business Informatics and Mathematics > Semantic Web (Juniorprofessur) (Ponzetto 2013-2015)
School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Keywords (English): text simplification , quality assessment , machine translation
Abstract: We investigate whether it is possible to automatically evaluate the output of automatic text simplification (ATS) systems by using automatic metrics designed for evaluation of machine translation (MT) outputs. In the first step, we select a set of the most promising metrics based on the Pearson’s correlation coefficients between those metrics and human scores for the overall quality of automatically simplified sentences. Next, we build eight classifiers on the training dataset using the subset of 13 most promising metrics as features, and apply two best classifiers on the test set. Additionally, we apply an attribute selection algorithm to further select best subset of features for our classification experiments. Finally, we report on the success of our systems in the shared task and report on confusion matrices which can help to gain better insights into the most challenging problems of this task.
Additional information: Online-Ressource

Dieser Eintrag ist Teil der Universitätsbibliographie.

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