Translation memory
30th August 2016
Types of Translation Memory systems
30th August 2016

Using translation memories

The program breaks the source text (the text to be translated) into segments, looks for matches between segments and the source half of previously translated source-target pairs stored in a translation memory, and presents such matching pairs as translation candidates. The translator can accept a candidate, replace it with a fresh translation, or modify it to match the source. In the last two cases, the new or modified translation goes into the database.

Some translation memories systems search for 100% matches only, that is to say that they can only retrieve segments of text that match entries in the database exactly, while others employ fuzzy matching algorithms to retrieve similar segments, which are presented to the translator with differences flagged. It is important to note that typical translation memory systems only search for text in the source segment.

The flexibility and robustness of the matching algorithm largely determine the performance of the translation memory, although for some applications the recall rate of exact matches can be high enough to justify the 100%-match approach.

Segments where no match is found will have to be translated by the translator manually. These newly translated segments are stored in the database where they can be used for future translations as well as repetitions of that segment in the current text.

Translation memories work best on texts which are highly repetitive, such as technical manuals. They are also helpful for translating incremental changes in a previously translated document, corresponding, for example, to minor changes in a new version of a user manual. Traditionally, translation memories have not been considered appropriate for literary or creative texts, for the simple reason that there is so little repetition in the language used. However, others find them of value even for non-repetitive texts, because the database resources created have value for concordance searches to determine appropriate usage of terms, for quality assurance (no empty segments), and the simplification of the review process (source and target segment are always displayed together while translators have to work with two documents in a traditional review environment).

If a translation memory system is used consistently on appropriate texts over a period of time, it can save translators considerable work.

Main benefits

Translation memory managers are most suitable for translating technical documentation and documents containing specialized vocabularies. Their benefits include:

  • Ensuring that the document is completely translated (translation memories do not accept empty target segments)
  • Ensuring that the translated documents are consistent, including common definitions, phrasings and terminology. This is important when different translators are working on a single project.
  • Enabling translators to translate documents in a wide variety of formats without having to own the software typically required to process these formats.
  • Accelerating the overall translation process; since translation memories “remember” previously translated material, translators have to translate it only once.
  • Reducing costs of long-term translation projects; for example the text of manuals, warning messages or series of documents needs to be translated only once and can be used several times.
  • For large documentation projects, savings (in time or money) thanks to the use of a TM package may already be apparent even for the first translation of a new project, but normally such savings are only apparent when translating subsequent versions of a project that was translated before using translation memory.

Main obstacles

The main problems hindering wider use of translation memory managers include:

  • The concept of “translation memories” is based on the premise that sentences used in previous translations can be “recycled”. However, a guiding principle of translation is that the translator must translate the message of the text, and not its component sentences.
  • Translation memory managers do not easily fit into existing translation or localization processes. In order to take advantage of TM technology, the translation processes must be redesigned.
  • Translation memory managers do not presently support all documentation formats, and filters may not exist to support all file types.
  • There is a learning curve associated with using translation memory managers, and the programs must be customized for greatest effectiveness.
  • In cases where all or part of the translation process is outsourced or handled by freelance translators working off-site, the off-site workers require special tools to be able to work with the texts generated by the translation memory manager.
  • Full versions of many translation memory managers can cost from US$500 to US$2,500 per seat, which can represent a considerable investment (although lower cost programs are also available). However, some developers produce free or low-cost versions of their tools with reduced feature sets that individual translators can use to work on projects set up with full versions of those tools. (Note that there are freeware and shareware TM packages available, but none of these has yet gained a large market share.)
  • The costs involved in importing the user’s past translations into the translation memory database, training, as well as any add-on products may also represent a considerable investment.
  • Maintenance of translation memory databases still tends to be a manual process in most cases, and failure to maintain them can result in significantly decreased usability and quality of TM matches.
  • As stated previously, translation memory managers may not be suitable for text that lacks internal repetition or which does not contain unchanged portions between revisions. Technical text is generally best suited for translation memory, while marketing or creative texts will be less suitable.

Effects on quality

The use of TM systems might have an effect on the quality of the texts translated. Its main effect is clearly related to the so-called “error propagation”: if the translation for a particular segment is incorrect, it is in fact more likely that the incorrect translation will be reused the next time the same source text, or a similar source text, is translated, thereby perpetuating the error.

Traditionally, two main effects on the quality of translated texts have been described: the “sentence-salad” effect (Bédard 2000; cited in O’Hagan 2009: 50) and the “peep-hole” effect (Heyn 1998). The first refers to a lack of coherence at the text level when a text is translated using sentences from a TM which have been translated by different translators with different styles. According to the latter, translators may adapt their style to the use of TMs in order for these not to contain intratextual references, so that the segments can be better reused in future texts, thus affecting cohesion and readability (O’Hagan 2009).

There is a potential, and, if present, probably an unconscious effect on the translated text. Different languages use different sequences for the logical elements within a sentence and a translator presented with a multiple clause sentence that is half translated is less likely to completely rebuild a sentence. Consistent empirical evidences (Martín-Mor 2011) show that translators will most likely modify the structure of a multiple clause sentence when working with a text processor rather than with a TM system.

There is also a potential for the translator to deal with the text mechanically sentence-by-sentence, instead of focusing on how each sentence relates to those around it and to the text as a whole. Researchers (Dragsted 2004) have identified this effect, which relates to the Automatic Segmentation feature of these programs, but it does not necessarily have a negative effect on the quality of translations.

Note that these effects are closely related to training rather than inherent to the tool. According to Martín-Mor (2011), the use of TM systems does have an effect on the quality of the translated texts, especially on novices, but experienced translators are able to avoid it. Pym (2013) reminds that “translators using TM/MT tend to revise each segment as they go along, allowing little time for a final revision of the whole text at the end”, which might in fact be the ultimate cause of some of the effects described here.

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