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Syntax-semantics interactions – seeking evidence from a synchronic analysis of 38 languages [version 1; peer review: 1 approved] ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: scripts repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: dataset repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: dataset repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: scripts repository ...
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Syntax-semantics interactions – seeking evidence froma synchronic analysis of 38 languages: scripts repository ...
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Automatic classification of human translation and machine translation : a study from the perspective of lexical diversity
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Abstract:
By using a trigram model and fine-tuning a pretrained BERT model for sequence classification, we show that machine translation and human translation can be classified with an accuracy above chance level, which suggests that machine translation and human translation are different in a systematic way. The classification accuracy of machine translation is much higher than of human translation. We show that this may be explained by the difference in lexical diversity between machine translation and human translation. If machine translation has independent patterns from human translation, automatic metrics which measure the deviation of machine translation from human translation may conflate difference with quality. Our experiment with two different types of automatic metrics shows correlation with the result of the classification task. Therefore, we suggest the difference in lexical diversity between machine translation and human translation be given more attention in machine translation evaluation. ; Publisher PDF
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Keyword:
3rd-DAS; Artificial Intelligence; Q Science (General); Q1
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URL: https://aclanthology.org/previews/ingest-nodalida/2021.motra-1.10/ http://hdl.handle.net/10023/23304
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Registerial Adaptation vs. Innovation Across Situational Contexts: 18th Century Women in Transition
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In: Front Artif Intell (2021)
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Syntax-semantics interactions – seeking evidence from a synchronic analysis of 38 languages [version 1; peer review: 1 approved]
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Linguistic Variation and Change in 250 Years of English Scientific Writing: A Data-Driven Approach
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In: Front Artif Intell (2020)
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What Do Neural Networks Actually Learn, When They Learn to Identify Idioms?
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In: Proceedings of the Society for Computation in Linguistics (2019)
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Enhancing the Accuracy of Ancient Greek WordNet by Multilingual Distributional Semantics
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In: Second Italian Conference on Computational Linguistics CLiC-it 2015 ; Proceedings of the Second Italian Conference onComputational Linguistics ; https://hal.archives-ouvertes.fr/hal-03167983 ; Proceedings of the Second Italian Conference onComputational Linguistics, 2015, Trento, Italy (2015)
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Contextual Distribution for Textual Alignment
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In: World Academy of Science, Engineering and TechnologyInternational Journal of Cognitive and Language Sciences ; https://hal.archives-ouvertes.fr/hal-03167990 ; World Academy of Science, Engineering and TechnologyInternational Journal of Cognitive and Language Sciences, 2015, Paris, France (2015)
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Linguistic Variation and Change in 250 Years of English Scientific Writing: A Data-Driven Approach [Online resource]
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IDS-Repository
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Less is more/more diverse: On the communicative utility of linguistic conventionalization [Online resource]
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IDS-Repository
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