JOURNAL ARTICLE

Translation as de- and reconstructing synsemiotic relationships: Contextual dimensions of opera libretto translation.

  • Published In: Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción, 2024, v. 70, n. 1-2. P. 17 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Agnetta, Marco 3 of 3

Abstract

In order to describe the nature of opera as a polysemiotic artifact and to address the challenges around its transfer, reference is often made to the concept of "context," which, however, is usually used rather casually and intuitively and is rarely defined precisely. Building on the theory of synsemioticity, a somewhat tighter analytical grid will be presented that allows the extension of context to become clearer. This is achieved in two ways: first, the status of nonverbal in the polysemiotic artifact is addressed, which, referring to Catford, must be defined as co-text rather than as context. Second, it will be shown on which semiotic levels contextuality can be described. The examples given here are taken from the opera Orfeo ed Euridice (1762) by Christoph Willibald Gluck and from some of the translations in German and French based on this work. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción. 2024/01, Vol. 70, Issue 1-2, p17
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2024
  • ISSN:0521-9744
  • DOI:10.1075/babel.00371.agn
  • Accession Number:175793548
  • Copyright Statement:Copyright of Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.