[PDF] Top 20 Using Contextual Information for Machine Translation Evaluation
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Using Contextual Information for Machine Translation Evaluation
... Automatic evaluation of Machine Translation (MT) is typically approached by measuring similarity between the candidate MT and a human reference ...existing evaluation systems is that they are ... See full document
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A Contextual Language Model to Improve Machine Translation of Pronouns by Re ranking Translation Hypotheses
... that using solely the PLM scores is inadequate. Using information from anaphora resolution, or at least from features that are relevant anaphora resolution, should help address these ... See full document
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Soft Contextual Data Augmentation for Neural Machine Translation
... its contextual mixture of multiple related ...tual information of the word to be replaced, the newly generated sentences capture much richer information than previous augmenta- tion ...scale ... See full document
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Information Based Machine Translation
... evaluated using a new corpus of unseen expressions with the verb to ...The evaluation data was collected from three different travel phrase books published by Barron, Berlitz, and Lonely ...resulting ... See full document
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First Steps in Using Word Senses as Contextual Features in Maxent Models for Machine Translation
... As a possible explanation for this outcome, we consider that not all of the open class words UKB tries to disambiguate will be assigned an appropriate synset identifier – a particular word may not have had an entry in ... See full document
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Phrase Based Evaluation for Machine Translation
... years, machine translation (MT) has benefited a lot from the advancement of automatic evaluation which, compared with manual evaluation, can give quick and objective feedback on the quality of ... See full document
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DTED: Evaluation of Machine Translation Structure Using Dependency Parsing and Tree Edit Distance
... While we have implemented a number of variants of DTED, for WMT 2015 and WMT 2016 we use only the ‘Pure’ version which processes only the structure of the sentences while ignoring other in- formation such as word ... See full document
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DiscoTK: Using Discourse Structure for Machine Translation Evaluation
... the information embedded in the discourse-trees (DTs) to compare the output of an MT system to a human ...translations using a convolution tree kernel (Collins and Duffy, 2001), which efficiently computes ... See full document
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Machine Translation Evaluation using Recurrent Neural Networks
... of information seen in a bigger ...the information sequen- tially whereas Tree-LSTM architectures enable sentence representation through a syntactic struc- ... See full document
5
Comparing a Hand crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation
... automatic evaluation of machine translation (MT) has proven to be a very significant research ...automatic evaluation methods focus on the evalua- tion of the output of MT as they compute ... See full document
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Using Discourse Structure Improves Machine Translation Evaluation
... reference translation provides additional in- formation that can be valuable for evaluating MT ...(human) translation, and (b) and (c) for transla- tions of two different systems on the WMT12 test ... See full document
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Quality Estimation for Machine Translation Using the Joint Method of Evaluation Criteria and Statistical Modeling
... SMT evaluation method on sen- tence ...MT evaluation utilizing the regression learning and based on a set of weaker indicators of fluency and adequacy as pseudo ...traditional machine ... See full document
8
Machine Translationness: Machine-likeness in Machine Translation Evaluation
... an evaluation method that as- sesses machine translations according to what they are (translations produced by a machine) and not to what they resemble (human ...the machine qualities of ... 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
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Diagnostic Evaluation of Machine Translation Systems Using Automatically Constructed Linguistic Check Points
... There are many differences between these n- gram based methods and our approach. In n- gram approach, a sentence is viewed as a collec- tion of n-grams with different length without dif- ferentiating the specific ... See full document
8
Effective Use of Linguistic and Contextual Information for Statistical Machine Translation
... Tables 1 and 2 show the BLEU and TER per- centage scores on MT06 and MT08 for Arabic- to-English and Chinese-to-English translation re- spectively. The context LM feature, the length feature and the syntax label ... See full document
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Putting Evaluation in Context: Contextual Embeddings Improve Machine Translation Evaluation
... MT evaluation (Pad´o et al., 2009): a good translation entails the reference and vice- ...irrelevant/wrong translation would be neutral/contradictory compared to the ... See full document
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Towards Machine Translation Using Contextual Information
... Towards Machine Translation Using Contextual Information Towards Machine ]ranslal; on U inf C, onC(,?t, m,1 hfforma,tion T i m C o r n i s h , K i m i k a z u ] " u j i t a , [ l y o c h i , ~ u g i n[.] ... See full document
6
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
11
Proceedings of the Human Informed Translation and Interpreting Technology Workshop (HiT IT 2019)
... the translation process, and of assisting human ...Assisted Translation (CAT) tools, electronic dictionaries, concordancers, spell-checkers, terminological databases, terminology extraction tools, ... See full document
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