New article published

2022-07-06

We are happy to announce that a new article has been published in JAT: Schaeffer-Lacroix, E., & Berland, K. (2022). Dealing with Variation in Audio Description Scripts. Journal of Audiovisual Translation5(1), 150–165. https://doi.org/10.47476/jat.v5i1.2022.181

 

Abstract

Audio description scripts represent a text type structured into several parts helping the speaker produce their recording. The heterogeneous composition and formatting of these parts makes it difficult to describe the linguistic features of audio description (AD) scripts in one go. Hence, it seems useful to implement them into a corpus tool enabling the analysis of the specificities of each AD section. In this paper, the AD scripts of 69 episodes from a German television show serve as a sample to explore a method for dealing with variation when preparing AD scripts for corpus processing. In our article, we offer a short overview of existing research on AD script corpora and on variation, and we present our dataset and the tools we used to prepare and explore the data. We then outline the features of the analysed AD scripts and the treatments applied. In the last section of the article, we discuss our results. Our analysis leads us to conclude that modifying original data for the sake of corpus implementation (e.g. changing formatting features) is a weighty step which may have unforeseen consequences: formal variation in AD scripts conveys more meaning than expected.

Lay summary

Audio description (AD) is a cultural technique helping blind people to enjoy going to the movies despite their disability. An additional soundtrack provides them with the information necessary to understand the essential action of the film.

The scripts of such soundtracks are mostly written by authors specialising in audiovisual translation. We were interested in the formatting features of such texts, called AD scripts, e.g. the use of bold print or of words entirely written in capital letters.

We conducted the study reported in this article because we wanted to know which sorts of variation can be identified in AD scripts. We also wanted to understand to which extent some of the varying features should be modified to improve text quality.

That is why we collected the AD scripts of 69 episodes of a German TV show (we got the rights to use them for our research). These texts were written by 13 AD authors over a period of 6 years. The broadcaster is the only stable parameter. With the help of text statistics tools, we found out that these AD scripts vary a lot from one author to another and even over time in the scripts written by one and the same author.

We modified our texts in order to unify some of their formatting features. However, we understood that reducing variation in AD scripts is not in any case a good option: the voice talents responsible for recording these scripts need clear and sufficient information to know how to proceed. In addition, AD script writing is a creative activity which should not be locked into strict rules.

  Author Biographies Eva Schaeffer-Lacroix, Sorbonne Université

Eva Schaeffer-Lacroix is a senior lecturer at the Department of Education of Sorbonne Université (Paris, France), where she teaches applied linguistics, ICT (Information and Communications Technology), and German as a foreign language. Her main research interests are corpus linguistics, writing in a foreign language, audio description and translation.

Kirsten Berland, INALCO, Paris

Kirsten Berland obtained in 2020 a bachelor’s degree in Korean Language and Multilingual Natural Language Processing at the INALCO (Institut National des Langues et Civilisations Orientales) in Paris. She is currently enrolled in the first year of a master’s degree in Natural Language Processing at the same university. In spring 2020, she collaborated with Eva Schaeffer-Lacroix (Sorbonne Université) to annotate a German audio description script dataset with XML-TEI (P5) during a one month’s internship at the research unit CeLiSo (Centre de Linguistique en Sorbonne).