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[PDF] Top 20 Measuring Machine Translation Errors in New Domains

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Measuring Machine Translation Errors in New Domains

Measuring Machine Translation Errors in New Domains

... alignment errors may affect its accuracy. Such errors are obvious in manually inspecting sentence triples using the ...alignment errors affect WADE, a French speaker manually corrected the word ali- ... See full document

12

Goodness: A Method for Measuring Machine Translation Confidence

Goodness: A Method for Measuring Machine Translation Confidence

... In this paper we proposed a method to predict con- fidence scores for machine translated words and sen- tences based on a feature-rich classifier using linguistic and context features. Our major contributions are ... See full document

9

Measuring Immediate Adaptation Performance for Neural Machine Translation

Measuring Immediate Adaptation Performance for Neural Machine Translation

... adaptive machine translation sys- tems, perceived adaptation performance is a cru- cial property: An error in the machine transla- tion output which needs to be corrected multiple times can cause ... See full document

9

Measuring the Effect of Conversational Aspects on Machine Translation Quality

Measuring the Effect of Conversational Aspects on Machine Translation Quality

... Next, after running the alignment process, we favor high-quality alignments by selecting only movies or movie versions (OpenSubtitles typically contains several alternative versions for a single movie (Tiedemann, 2016)) ... See full document

11

Five Shades of Noise: Analyzing Machine Translation Errors in User Generated Text

Five Shades of Noise: Analyzing Machine Translation Errors in User Generated Text

... Most state-of-the-art SMT systems, including our in-house system, are phrase-based, with transla- tions being generated phrase by phrase rather than word by word (Koehn et al., 2003). An abundant use of small phrases ... See full document

10

Measuring ‘Registerness’ in Human and Machine Translation: A Text Classification Approach

Measuring ‘Registerness’ in Human and Machine Translation: A Text Classification Approach

... man translation characteristics in MT are often considered to be beneficial as they can improve the BLEU scores, we believe that the application of human translation as a reference should be treated with ... See full document

10

Assessing the Impact of Translation Errors on Machine Translation Quality with Mixed effects Models

Assessing the Impact of Translation Errors on Machine Translation Quality with Mixed effects Models

... and domains, have been used to determine the qual- ity of translations according to the amount of er- rors encountered (Popovic et ...design new automatic metrics that take into considera- tion human ... See full document

11

Phrase Level Segmentation and Labelling of Machine Translation Errors

Phrase Level Segmentation and Labelling of Machine Translation Errors

... The second scenario is more flexible: it is able to generate a segmentation for all sentences. However, similarly to the source-target approach, it depends on the data, in particular, on the training data of the SMT ... See full document

6

Proceedings of the First Conference on Machine Translation: Volume 1, Research Papers

Proceedings of the First Conference on Machine Translation: Volume 1, Research Papers

... five translation tasks: Machine Translation of News, Machine Translation of IT domain, Biomedical Translation, Multimodal Machine Translation, and Cross-lingual ... See full document

28

Analysis of Machine Translation Systems’ Errors in Tense, Aspect, and Modality

Analysis of Machine Translation Systems’ Errors in Tense, Aspect, and Modality

... the translation of tense, aspect, and modality by machine translation systems were analyzed for six translation systems on the market and our new systems for translating tense, aspect, ... See full document

12

Collaborative Machine Translation Service for Scientific texts

Collaborative Machine Translation Service for Scientific texts

... yielded a gain of more than 7 BLEU points, in both domains (computer science and physics). In- cluding the theses abstracts in the parallel training corpus, a further gain of 2.3 BLEU points is ob- served for ... See full document

5

Measuring the Impact of Spelling Errors on the Quality of Machine Translation

Measuring the Impact of Spelling Errors on the Quality of Machine Translation

... of translation considering only the difference between original sets of ...the translation result. This may occur in cases of minor errors, such as, for instance, missing ...in translation, ... See full document

7

Machine Translation Quality Estimation Across Domains

Machine Translation Quality Estimation Across Domains

... From left to right, each column represents News, TED, and IT domains, respectively, while each row is the instantiation of a feature in the corresponding task. Columns with non-black entries represent outlier ... See full document

12

Squibs and Discussions: Measuring Word Alignment Quality for Statistical Machine Translation

Squibs and Discussions: Measuring Word Alignment Quality for Statistical Machine Translation

... phrase translation lexicon (which maps source phrases to target phrases using counts from the word alignment) and some of the word level translation parameters (sometimes called lexical ... See full document

12

IDENTIFICATION AND CORRECTION OF COORDINATE MEASURING MACHINE GEOMETRICAL ERRORS USING LASERTRACER SYSTEMS

IDENTIFICATION AND CORRECTION OF COORDINATE MEASURING MACHINE GEOMETRICAL ERRORS USING LASERTRACER SYSTEMS

... Geometric errors can be also expressed us- ing standards of ...kinematic errors compo- nents, including the information about CMMs geometric ...of errors in the entire three-dimensional ... See full document

6

Machine Translation Again?

Machine Translation Again?

... Machine Translation Again? Machine Translation Again? Yorick Wilks, Jaime Carbonen, David Farwell, Eduard Hovy and Sergei Nirenburg Department of Computer Science New Mexico State University Las Cruce[.] ... See full document

8

Building a Corpus of Errors and Quality in Machine Translation: Experiments on Error Impact

Building a Corpus of Errors and Quality in Machine Translation: Experiments on Error Impact

... of errors (such as ...with errors and translation quality, will allow to find out these weights empirically, ob- serving from data which errors most affect ... See full document

5

Non-Autoregressive Machine Translation with Auxiliary Regularization

Non-Autoregressive Machine Translation with Auxiliary Regularization

... • Sequence level knowledge distillation. NAT model is typ- ically trained with the help from an autoregressive trans- lation (AT) model as its teacher. The knowledge of the AT model is distilled to the NAT model via the ... See full document

8

An analysis of machine translation errors on the effectiveness of an Arabic-English QA system

An analysis of machine translation errors on the effectiveness of an Arabic-English QA system

... AnswerFinder was able to answer 23 trans- lated questions out of 199. Out of these 23 ques- tions, 12 were correctly translated and 11 exhib- ited some translation errors. Looking closely at the 12 ... See full document

7

Learning to translate with products of novices: a suite of open ended challenge problems for teaching MT

Learning to translate with products of novices: a suite of open ended challenge problems for teaching MT

... chine translation should be good paraphrases of each other (Owczarzak et ...between machine translation and reference under a simple model in which words could align if they were ... See full document

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