• Nina Meki Fatimah and Reza Dwi Wijayanti

APPLYING FAR MODEL SUBTITLING QUALITY ASSESSMENT BY JAN PEDERSEN IN THE SWEARING OF “RUSH HOUR 3 M


Abstract

This research discusses the subtitle (Translation assessment) on a swearing sentence at Rush Hour 3 movie. The study of subtitling is translated a language from English as a source text to Indonesia as a target text. This study related to the analyses of subtitling quality assessment in terms of functional equivalence; semantic errors, stylistic errors, acceptability; grammar errors; spelling errors; idiomaticity errors, and readability; segmentation and spotting; punctuation and graphics; reading speed and line length. This research uses descriptive qualitative research. The findings result of this research are 44 data, there are functional equivalent (98%): semantic errors (2%); stylistic errors (0%), acceptability (77%): grammar errors (0%); spelling errors (0%); idiomaticity errors (23%), readability (88%): segmentation and spotting (6%); punctuation and graphics (2%); reading speed and line length (2%). The data are categorized as functional equivalence, acceptability, and readability in subtitling quality assessment.

Keywords: Translation, Subtitling, Subtitling quality, Audiovisual translation, Swearing, FAR Model.

  1. Introduction

Nowadays, film has been one of subject of research study in Translation. Translation is the process of transfering meaning by source language to target language. According to Catford (1969:20) translation is the replacement of textual material in one language by equivalent textual material in another language. Base on the definition texts in different languages can be equivalent in different degrees (fully or partially equivalent), in respect of different levels of presentation (equivalent in respect of context, of semantics, of grammar, etc.) and different ranks (word for word, phrase for phrase, sentence for sentence). Nida and Taber (1969:12) have definition if translation consists of reproducing in the receptor language the closest natural equivalence of the source language message, first in terms of meaning and secondly in terms of style. From the definition above they are mention about equivalent in translation. The meaning in both of the source to emphasize if the message of source language must equivalent and transferring the meaning clearly.

Translation in film exists in the form of subtitling. According to Sacconi,Susanna(2013 in Karamittroglou 2002) subtitling is the translation of the spoken (or written) source text of an audiovisual product into a written target text which is added onto the image of the original product, usually at the bottom of the screen. Others expert Jorge Diaz C and Gunilla Anderman (2008 in Luyken et al 1991) define it as ...condensed written translations of original dialogue which appear as lines of text, usually positioned towards the foot of the screen. Subtitles appear and disappear to coincide in time with the corresponding portion of the original dialogue and are almost always added to the screen image at a later date as a post-production activity.

Subtitling is also a type of audiovisual translation that has its own specifications, rules and criteria. Audiovisual Translation is a tool to help other people in their situation when they can’t hear, see or need a special treatment. That way uses to make them more informative and translate one language to other language. Like when they are watching television and can’t hear the audio. So, the party of TV used subtitling or other technical. According to Heiss (1996:15 in Susanna, Sacconi. 2013) defines audiovisual translation as the elaboration of a multimedia product and not only of its linguistic component.

In the case of subtitling it is limited by space and time. Subtitle is captions displayed at the bottom of a movie or television screen that translate or transcribe the dialogue or narrative. Subtitle exist in every genre of films, two of them are comedy and action. One of many films that employ a lot of humorous nuance and action is Rush Hour 3 directed by Brett Ratner. The Rush Hour 3 is chosen to be the object of this research because it exploits of swear word. Acording to (Timothy Jay and Kristin Janschewitz, 2006) have demonstrated that swearing in public is not an infrequent act, and most instances of swearing are conversational; they are not highly emotional, confrontational, rude, or aggressive. Through thousands of incidents of recorded swearing, we have never witnessed any form of physical aggression as a consequence of swearing.

The translation of Rush Hour 3 Movie can be seen through its subtitling. Therefore, this research will discuss the Translation Quality Assessment as Subtitling Quality Assessment that focuses on the criteria of assesses the swearing sentence in the subtitle movie. From the definition above the researcher argue if swearing can be polite or impolite. Juliane House defined in his book Translation Quality Assessment; it is an invaluable resource for students and researchers of translation studies and intercultural communication, as well as for professional translators.

In this research, the researcher uses a FAR model from Jan Pedersen which discuses about subtitling quality assessment. There are criteria of the FAR model such as functional equivalence, acceptability, and readability. Every criteria has a next criteria as functional equivalence with semantic errors and stylistic errors; acceptability with grammar errors, spelling errors, and idiomaticity errors, readability with segmentation and spotting, punctuation and graphics, reading speed and line length. The researcher only focusses in assessing translation and suntitling quality of swearing in Rush Hour 3 movie.

  1. Research Methodology

The researchers in this study as the raters collected the data for the evaluation and analyzing the data. This research was not an experimental type, but a descriptive and qualitative one; therefore, there were no participant. The material of this study consisted of 44 data swearing sentence in Rush Hour 3 movie. The data were gathered by the researchers directly by observing the subtitle in the movie. They have categorized the data. The researchers assesses subtitle quality used FAR model. The FAR model has three areas, there are: functional equivalence, acceptability, and readability.

  1. Result and discussion

The 44 data of swearing sentence found in the dialogue in Rush Hour 3 movie. The researchers assesses subtitle quality used FAR model. The FAR model has three areas, there are: functional equivalence, acceptability, and readability.

Functional equivalence, ideally, a subtitle would convey both what is said and what is meant. If neither what is said nor what is meant is rendered, the result would be an obvious error. If only what is meant is conveyed, this is not an error; it is just standard subtitling practice, and could be preferred to verbatim renderings. If only what is said is rendered (and not what is meant), that would be counted as an error too, because that would be misleading. Equivalence errors are of two kinds: semantic and stylistic (Pederson, 2017: 218).

Functional Equivalence

Frequency

Percentage

Functional Equivalence

43

98%

Semantic errors

1

2%

Stylistic errors

0

0%

Total

44

100%

The example of functional equivalence:

SL: Listen, that's a badass suit. Let's get the hell outta here.

TL: Disitu ada kopo baju. Ayo kita pergi dari sini.

The data is the example of semantic errors; “kopo” is an error. In the data above the researcher found an error in the functional equivalence error in semantic error. The example showed semantic error from the translator means kopor but in the screen typo became “kopo”. This error made viewer misunderstanding about the plot of the movie.

Acceptability is one of the important thing in FAR model because it is establish the text acceptable or not. If the viewer accepts and know the meaning of the text, it means the text is acceptable. Furthermore acceptability is the subtitles sound foreign or otherwise unnatural. Acceptability error is the idea of the acceptability not arrive on the viewer and there is an error in the delevery an idea. There are three kinds of acceptability: grammar, spelling and idiomaticity.

The example of acceptability:

SL: What the hell?

TL: Ada apa ini?

The data above is the example of idiomaticity. The researcher found a acceptability error in idiomaticity error. Indiomaticity error doesn’t discus about idiom but the natural translate of the target text. The translator convey the meaning of the text appropriate or not with the situation in the dialogue. In the source language “what the hell?” have a meaning as a swearing or using a emotional situation to say this one. But the translator just translate became “ada apa ini?”, it is reduce the sense of the situation in this movie. You should make the situation get angry not make it flat.

Acceptability

Frequency

Percentage

Acceptability

34

77%

Grammar errors

0

0%

Spelling errors

0

0%

Idiomaticity errors

10

23%

Total

44

100%

Readability is the last categorize of the FAR model. It discuses about how the viewer can read the subtitle clearly. If the viewer can read as well as the target language, that target text in subtitles is readability. And there are some errors as segmentation and spotting, punctuation and graphics, reading speed and line length.

SL: Why the hell you give mean empty gun, then?

TL: Lalu, mengapa kau berikan aku senjata yang tak ada pelurunya.

This data above is the example of punctuation and graphics error. The researcher found readability error in punctuation and graphics error. Punctuation and graphics is discus about punctuation in subtitle because punctuation is very important for the viewer, with punctuation the viewer can show the situation as question, angry, etc. From the example above the translator delete the punctuation of “?”, it makes the reduce the sense of situation that ask something became statement.

Readability

Frequency

Percentage

Readability

39

88%

Segmentation and spotting

3

6%

Punctuation and graphics

1

3%

Reading speed and line length

1

3%

Total

44

100%

4. Conclusion

From the data above the researcher found 44 data of swearing in the Rush Hour 3 Movie. The researcher analysis the data used Pederson’s theory which called FAR model. In this theory discus about the subtitling quality assessment and the researcher mix with the quality in translation. The clasisification in FAR model are functional equivalence, acceptability and readability. And the crieteria of each class as functional equivalence: semantic errors and stylistic errors; acceptability: grammar errors, spelling errors and idiomaticity errors; readability: segmentation and spotting, punctuation and graphics, reading speed and line length. There are 44 data and the details are functional equivalent (98%): semantic errors (2%); stylistic errors (0%), acceptability (77%): grammar errors (0%); spelling errors (0%); idiomaticity errors (23%), readability (88%): segmentation and spotting (6%); punctuation and graphics (2%); reading speed and line length (2%). The researcher found an analysis of the swearing in funtional equivalenve, acceptability, and readability is acceptable. However, there are several errors of accetability in idiomaticity.

Blibiography

Nida, E. A., & Taber, C. R. (2003). The theory and practice of translation (Vol. 8). Brill.

Catford, J. C. (1978). A linguistic theory of translation. Oxford University Press,.

Cintas, J. D., & Anderman, G. (Eds.). (2008). Audiovisual translation: Language transfer on screen. Springer.

Sacconi, S. (2013). " How The Nanny has become La Tata": analysis of an audiovisual translation product.

Pedersen, J. (2017). The FAR model: assessing quality in interlingual subtitling. Journal of Specialised Translation, (28), 210-229.

Jay, T., & Janschewitz, K. (2008). The pragmatics of swearing. Journal of Politeness Research. Language, Behaviour, Culture, 4(2), 267-288.

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