title: Interdependence of expert categories and automated metrics applied to evaluate translation quality
metadata.name: dc.contributor.author
metadata.value: Sosnin, Alexey V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Balakina, Julia V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Kashikhin, Andrey N.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2022-08-10T16:51:58Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2022-08-10T16:51:58Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2022-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Ѕоsnin A. V., Baӏakina Јu. V., Kashikhin A. N. Interdependence of expert categories and automated metrics applied to evaluate translation quality. Vestnik of Saint Petersburg University. Language and Literature. 2022, 19 (1): 125–148.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu09.2022.107
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/37323
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The article evaluates the quality of translation; we consider the applied and pragmatic aspects
  of such evaluation in the conditions of the current rapid increase in the number of texts to be
  translated. The article summarizes a plethora of assessment principles, each having its merits
  and drawbacks, and examines the correlation between the categories of adequacy and equivalence
  as the basic assessment parameters. We conclude that equivalence is oriented towards
  the result of translation, whereas adequacy indicates whether translation as process corresponds
  to the communicative situation given. Adequacy is thus viewed as a discursive feature.
  The article also looks into the possibility of applying these assessment criteria to automated
  evaluation of translation quality, and compares the specific computer metrics or, algorithms:
  Cosine Similarity, Word Error Rate, BLEU, ROUGE, NIST, METEOR. We analyze the potential
  for applying these metrics to man-made rather than machine translated. The n-gram metric
  for evaluation of translation with explicit ordering Meteor is the most efficient algorithm;
  however, it can only be applied advantageously to formal standardized texts. The article points
  out that literary translation can hardly be evaluated on the basis of n-gram correspondences
  due to it characteristic feature: ample use of non-equivalent units even at the sentence level.
  The purely mathematical procedures overviewed in the article cannot serve as linguistic metamodels
  of assessment unless supplemented with syntactic and semantic algorithms.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Language and Literature;Volume 19; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: evaluation of translation quality
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: adequacy
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: equivalence
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: machine translation
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: automated metrics for evaluation of translation
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: word embedding
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Interdependence of expert categories and automated metrics applied to evaluate translation quality
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 13508-Текст статьи-43907-1-10-20220511.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/37323/1/13508-%d0%a2%d0%b5%d0%ba%d1%81%d1%82%20%d1%81%d1%82%d0%b0%d1%82%d1%8c%d0%b8-43907-1-10-20220511.pdf
resources.format: Adobe PDF
resources.size: 923,36 kB