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explosion/spaCy: v3.3.0: Improved speed, new trainable lemmatizer, and pipelines for Finnish, Korean and Swedish ...
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explosion/spaCy: v3.3.0: Improved speed, new trainable lemmatizer, and pipelines for Finnish, Korean and Swedish ...
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huggingface/transformers: v4.4.0: S2T, M2M100, I-BERT, mBART-50, DeBERTa-v2, XLSR-Wav2Vec2 ...
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explosion/spaCy: v3.2.0: Registered scoring functions, Doc input, floret vectors and more ...
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Comparing the Effect of Product-Based Metrics on the Translation Process
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In: Front Psychol (2021)
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Abstract:
Characteristics of the translation product are often used in translation process research as predictors for cognitive load, and by extension translation difficulty. In the last decade, user-activity information such as eye-tracking data has been increasingly employed as an experimental tool for that purpose. In this paper, we take a similar approach. We look for significant effects that different predictors may have on three different eye-tracking measures: First Fixation Duration (duration of first fixation on a token), Eye-Key Span (duration between first fixation on a token and the first keystroke contributing to its translation), and Total Reading Time on source tokens (sum of fixations on a token). As predictors we make use of a set of established metrics involving (lexico)semantics and word order, while also investigating the effect of more recent ones concerning syntax, semantics or both. Our results show a, particularly late, positive effect of many of the proposed predictors, suggesting that both fine-grained metrics of syntactic phenomena (such as word reordering) as well as coarse-grained ones (encapsulating both syntactic and semantic information) contribute to translation difficulties. The effect on especially late measures may indicate that the linguistic phenomena that our metrics capture (e.g., word reordering) are resolved in later stages during cognitive processing such as problem-solving and revision.
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Keyword:
Psychology
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URL: http://www.ncbi.nlm.nih.gov/pubmed/34489795
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418076/
https://doi.org/10.3389/fpsyg.2021.681945
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huggingface/transformers: ProphetNet, Blenderbot, SqueezeBERT, DeBERTa ...
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huggingface/transformers: Trainer, TFTrainer, Multilingual BART, Encoder-decoder improvements, Generation Pipeline ...
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