The present chapter explores how corpus methods can be implemented in analysing the construction of characters in source and dubbed film dialogues. The English original and Italian dubbed cinematic adaptations of Little Women are taken as a case in point to showcase how film dialogues can be turned into a digital annotated parallel corpus to be used for systematic textual analyses across characters, film adaptations, and translations. The corpus-driven analysis on the original texts focuses on the implicit characterisation cues that are used to construct the identities of the four protagonists of the story, the March sisters. The translation solutions for some salient linguistic expressions in the English original versions (i.e. the vocative Marmee and some conversational routines in the form of apologies) are further evaluated through a parallel concordance analysis.

Exploring the construction and translation of film characters through a parallel corpus: The case of Little Women adaptations

Gianmarco Vignozzi
2022-01-01

Abstract

The present chapter explores how corpus methods can be implemented in analysing the construction of characters in source and dubbed film dialogues. The English original and Italian dubbed cinematic adaptations of Little Women are taken as a case in point to showcase how film dialogues can be turned into a digital annotated parallel corpus to be used for systematic textual analyses across characters, film adaptations, and translations. The corpus-driven analysis on the original texts focuses on the implicit characterisation cues that are used to construct the identities of the four protagonists of the story, the March sisters. The translation solutions for some salient linguistic expressions in the English original versions (i.e. the vocative Marmee and some conversational routines in the form of apologies) are further evaluated through a parallel concordance analysis.
2022
Vignozzi, Gianmarco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1135164
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