[PDF] Top 20 MAXSIM: A Maximum Similarity Metric for Machine Translation Evaluation
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MAXSIM: A Maximum Similarity Metric for Machine Translation Evaluation
... automatic machine translation (MT) evaluation metric that calculates a sim- ilarity score (based on precision and recall) of a pair of ...a similarity score between items across the two ... See full document
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ReVal: A Simple and Effective Machine Translation Evaluation Metric Based on Recurrent Neural Networks
... As we do not have access to any dataset which provides scores to segments on the basis of trans- lation quality, we used the WMT-13 ranks corpus to automatically derive training data. This corpus is a by-product of the ... See full document
7
Automatic Evaluation Metric for Machine Translation that is Independent of Sentence Length
... (A. Lavie and A. Agarwal, 2007) and MaxSim (Y. Seng Chan and H. Tou Ng, 2008) and the non-linguistic approach, which includes BLEU (K. Papineni et al., 2002), TER (M. Snover et al., 2006), RIBES (H. Isozaki et ... See full document
7
Learning the Impact of Machine Translation Evaluation Metrics for Semantic Textual Similarity
... MT evaluation metrics together with other lexi- cal and syntactic features to predict the semantic similarity scores in ...the evaluation metrics to the overall performance and how each metric ... See full document
6
Source Language Features and Maximum Correlation Training for Machine Translation Evaluation
... fluency evaluation results than ...SSCN metric, pSSCN u(2), achieves the best performance among all the testing metrics in overall and ade- quacy, and the second best performance in fluency, which is just a ... See full document
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Metric for Automatic Machine Translation Evaluation based on Universal Sentence Representations
... segment-level metric for automatic machine translation evaluation ...man evaluation enable the continuous integration and deployment of a machine translation (MT) ... See full document
6
Phrase Based Evaluation for Machine Translation
... the metric of NIST to score ...mutual similarity score is ...since similarity based on PER (Su et ...a translation and phrase correspondence relies on word-alignment trained on parallel ... See full document
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Designing a Frame Semantic Machine Translation Evaluation Metric
... As reported in (Čulo 2016), there are various strategies to deal with this when translating from German to English. The simplest would be to just switch the order of subject and object, losing the focus on ... See full document
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Beyond BLEU:Training Neural Machine Translation with Semantic Similarity
... exact metric, we reference the bur- geoning field of research aimed at measuring se- mantic textual similarity (STS) between two sen- tences (Le and Mikolov, 2014; Pham et ... See full document
12
Accurate semantic textual similarity for cleaning noisy parallel corpora using semantic machine translation evaluation metric: The NRC supervised submissions to the Parallel Corpus Filtering task
... SMT system using Portage (Larkin et al., 2010), a conventional log-linear phrase-based SMT sys- tem. The translation model of the SMT system uses IBM4 word alignments (Brown et al., 1993) with grow-diag-final-and ... See full document
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A New Syntactic Metric for Evaluation of Machine Translation
... syntactic metric for MT evaluation, we have incorporated the WCDG parser in the process of ...tree similarity metric applied on the two dependency parse trees would prove to be an efficient ... See full document
6
LAYERED: Metric for Machine Translation Evaluation
... Machine translation evaluation has always re- mained as the most popular measure to judge the quality of a system output compared to the refer- ence ...MT evaluation metric which is ... See full document
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Improving machine translation by training against an automatic semantic frame based evaluation metric
... adequate translation than tuning against BLEU or TER, as measured across all other commonly used metrics and human subjec- tive ...MT evaluation metric does pro- duce output which is adequate and ... See full document
7
Meteor 1 3: Automatic Metric for Reliable Optimization and Evaluation of Machine Translation Systems
... We have presented Ranking, Adequacy, and Tun- ing versions of Meteor 1.3. The Ranking and Ad- equacy versions are shown to have high correlation with human judgments except in cases of overfitting due to skewed tuning ... See full document
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Proceedings of the Human Informed Translation and Interpreting Technology Workshop (HiT IT 2019)
... Human-Informed Translation and Interpreting Technology (HiT-IT 2019) took place in Varna, Bulgaria and spanned over two days (5-6 September 2019), as a post-RANLP 2019 conference ... See full document
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Evaluation in the ARPA Machine Translation Program: 1993 Methodology
... Evaluation in the ARPA Machine Translation Program 1993 Methodology Evaluation in the ARPA Machine Translation Program John S White, Theresa A O'Connell PRC Inc M c L e a n , VA 22102 1993 Methodology[.] ... See full document
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Evaluation of Machine Translation
... EVALUATION OF MACHINE TRANSLATION E V A L U A T I O N O F M A C H I N E T R A N S L A T I O N John S White, Theresa A O'Connell P R C Inc M c L e a n , V A 2 2 1 0 2 a n d Lynn M Carlson D o D A B S T[.] ... See full document
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Machine Translationness: Machine-likeness in Machine Translation Evaluation
... make machine translations distinguishable from human ...MT evaluation method based on determining whether the translation is machine-like instead of determining its human-likeness as in ... See full document
8
Extending Machine Translation Evaluation Metrics with Lexical Cohesion to Document Level
... Previous researches in MT predominantly focus on specific types of cohesion devices. For grammat- ical cohesion, a series of works, including Nakaiwa and Ikehara (1992), Nakaiwa et al. (1995), and Nakaiwa and Shirai ... See full document
9
Human Evaluation of Neural Machine Translation: The Case of Deep Learning
... It is important to note that these typologies were established before the creation of NMT, and it could therefore be argued that they concentrate mostly on features for which more recent MT systems are not likely to ... See full document
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