Day: March 28, 2018

SDL Survey Results for Corporate Translation Technology Survey 2017

SDL Survey Results for Corporate Translation Technology Survey 2017

SDL published a new report contains the results of a survey about  Corporate Translation Technology Survey 2017 . The report starts with defining  the meaning of corporate included in this survey. By corporate, SDL means private- and public-sector organizations that are generating content to be translated. It therefore doesn’t include language service providers (translation agencies) or freelance translators.  As a result, this new survey reveals some answers to the question:


Given that cost is an ever-present issue for corporates, and that demand for translation continues to grow with no end in sight, just how are
corporates tackling their quest for quality in translation?

The survey covered the below regions with a total of 554 respondents from public and private sector corporates.

Quality Priority and Challenge:

The survey results confirm what we’ve learned before about quality and rising demand:

• Almost 9 out of 10 respondents agree that quality is much more important than cost.
• Maintaining quality also looms largest when they list their top challenges: now and in 5 years time.
• And the pressures of demand can clearly be seen in the other top challenges: shortened timelines and increased internal demand. These demand pressures are expected to be more of a challenge in 5 years.

The results shed light on the aforementioned challenges along with other challenges that face translation industry nowadays, such as:

  • Lack of qualified translators.
  • Educating stakeholders on the translation process.
  • Translation budgets not increasing in line with demand.
  • Increase in the number of language pairs to be translated.

The report tries to solve these challenges by asking  very important questions. The first question: “is outsourcing an answer?“. Then, it shows in numbers how respondents feel about and handle outsourcing and what are their different motives.

The second question: “is technology an answer?“. In this point, the survey results showed that  94% of respondents agree that they find translation technology vital to managing translation demand, and that two-thirds (66%) of respondents’ organizations use computer-assisted
translation (CAT). There are, however, significant regional differences in CAT use: it’s 73% for North America, 71% for Europe, and only 48% for APAC. 

CAT makes translators more productive, especially through the use of translation memory to speed up translation of content previously
encountered and simplify the re-use of quality work. How much of the content translated by your organization would you say is brand new vs previously translated? For the survey respondents, on average, it’s almost 50-50.

Speaking about technology and CAT tools, has led to an eventual question, is Machine Translation helpful or not?.  Indeed, 61% of respondents agree that machine translation is essential to coping with increasing translation demands. But only just over a quarter (28%) are using machine translation, with Europe (25%) lagging behind North America (35%) and APAC (31%).

Regarding the frequency of post-editing after using machine translation. Only 16% are occasionally, rarely or never post-editing, with 78% post-editing most or all of the time.

Then the report moves to terminology management tools and how they may help in the quality challenge. For corporates, maintaining quality in the face of increasing demand is not just about individual translation productivity, but at least as much about ensuring consistency across projects, translators, and the wider business. Terminology management tools help with consistency — but their value can only be fully realized if termbases can be efficiently shared.

The report ends with recommendations to solve some challenges such as outsourcing and machine translation.

To download the full report: https://goo.gl/L2vGZE

MemoQ’s First Release in 2018: MemoQ 8.4

MemoQ’s First Release in 2018: MemoQ 8.4

Kilgary released its MemoQ 8.4, its first release for 2018. Improvements come in five main areas: user experience, terminology, filters in memoQ, performance, and server workflows. Read on for details:

1- User Experience 

A- Customer Insights Program

The memoQ Customer Insights program will feature two major initiatives:

Usage Data Collection: When you work with memoQ, you are given the choice to enable sending data about how you use the software. Not all types of data will be collected. For more details, check here: https://goo.gl/fgppMh

The Design Lab: A loosely knit community where you can share your insights, opinions and knowledge. In exchange, we will evolve memoQ to be a user-friendly tool that meets your needs and solves your problems. For more details and how to join: https://goo.gl/dbHHeD

B- Comments in online projects

We have re-worked the way comments work in online projects. Now, project managers can delete any comments anywhere. And, non PM users can only delete their own comments. Also, users can edit their own comments only.

C- Task Tracker Progress Messages

In memoQ 8.4, Task Tracker progress messages are shown more consistently. From now on, the Task Tracker will display proper progress messages whenever TMs and TBs are exported. When you export a TM or TB, the message “In progress…” will be displayed as soon as the export begins, and “Done.” when the export completes.

In addition, you will be able to open the location where the export was saved by using the Open folder icon.

2- Terminology

A- Import and export term bases with images

With memoQ 8.4, you can now import and export term bases with images.

B- Forbidden terms in the spotlight

MemoQ 8.4 adds new functionality to work with forbidden terms more effectively and -transparently. It will be marked in the term editor for easy identification. It will be highlighted in red for exported and imported term bases.

C- Filters & QA settings

MemoQ 8.4 features small improvements that will facilitate the way you work with terminology while boosting efficiency. You can now determine which of the term bases assigned to the project you want to use for quality assurance in a specific project.

D- More effective stop word lists

MemoQ 8.4 improves stop word list functionality to make term extraction sessions more productive. By improving your stop word lists you can reduce the number of term candidates you need to process in a term extraction session.

E- Filter filed in term extraction

MemoQ 8.4 introduces a more user-friendly filter field on the term extraction screen featuring the history of the term extraction’s session.

F- Smart search settings in QTerm

From now on, when you log into QTerm, you will see the same settings you used the last time on the search page (term bases to search, view, languages, term matching). This is particularly useful if you typically use QTerm for term lookup in a specific language combination and/or with specific term bases.

G- Entry relationships in QTerm

If you establish a symmetrical (homonym, synonym, antonym, cohyponym) or an anti-symmetrical (hyponym, hypernym) entry relationship in one entry with another, the corresponding relationship is also created in the other entry.

H- Easy Term Search

MemoQ 8.4 now offers memoQWeb external users simple and easy access to QTerm term bases for lookup.

I- Filtering Options

The “Begins with” filter condition and search option has been revamped and it now features a more user-friendly term matching interface.

3- Performance

A- Improvements in responsiveness​

When you download memoQ 8.4, you will experience performance improvements in the following areas:
  • Opening the memoQ dashboard,
  • Opening projects,
  • Opening translation documents,
  • Scrolling through resources,
  • Faster rendering of various screens.
Note: The degree of improvements in performance you experience depends on your hardware configuration.

B- MemoQ server back-up

With memoQ 8.4, backing up your server should be faster. We have improved the performance of this task by decreasing back-up time by up to 50%.

Note: The improvement in backup duration may not be significant for memoQ Servers running on SSD drives.

4- Document Import and Export

A- Import filter for subtitles and dubbing script

The new import filter in memoQ 8.4 can handle two subtitle formats:

  • .srt files
  • custom-made .xlsx.

The preview displaying live video will be a plugin based on Preview SDK.

B- ZIP Filter

The new filter offers a generic option for handling ZIP packages. It will display the files of the archive as embedded documents. It will also be possible to import only some of them.

5- Server-to-server Workflows

A- Lookup on Enterprise TM

Until now, memoQ servers around the world resemble big powerful giants that are unable of “talking to each other”. This is now going to change.
MemoQ is investing effort in developing this new technology that will add significant value to customers using the following workflows:
  • Client + Vendor
  • Making use of several memoQ servers.

The projects created from packages now have direct access to the parent TMs. It is done through the child server, so firewalls can be configured to let the traffic through. Project Managers can deliver with one click.

Edit Distance in Translation Industry

Edit Distance in Translation Industry

In computational linguistics, edit distance or Levenshtein distance, is a way of quantifying how dissimilar two strings (e.g., words) are to one another by counting the minimum number of operations required to transform one string into the other.  The edit distance between (a, b) is the minimum-weight series of edit operations that transforms a into b. One of the simplest sets of edit operations is that defined by Levenshtein in 1966 which are:

1- Insertion.

2- Deletion

3- Substitution.

In Levenshtein’s original definition, each of these operations has unit cost (except that substitution of a character by itself has zero cost), so the Levenshtein distance is equal to the minimum number of operations required to transform a to b.

For example, the Levenshtein distance between “kitten” and “sitting” is 3. A minimal edit script that transforms the former into the latter is:

  • kitten – sitten (substitution of “s” for “k”).
  • sitten –  sittin (substitution of “i” for “e”).
  • sittin –  sitting (insertion of “g” at the end).

What are the application of edit distance in translation industry?

1- Spell Checkers

Edit distance is applied where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question.

2- Machine Translation Evaluation and Post Editing

Edit distance can be used to compare a postedited file to the machine translated output that was the starting point for the postediting. When you calculate the edit distance, you are calculating the “effort” that the posteditor made to improve the quality of the machine translation to a certain level. Starting from the source content and same MT output, if you perform a light postediting and a full postediting, the edit distance for each task will be different, and the human quality level is expected to have a higher edit distance, because more changes are needed. This means that you are measuring light and full postediting using the edit distance.

Therefore, the edit distance is a kind of “word count” measure of the effort, similar in a way to the word count used to quantify the work of translators throughout the localization industry. It also helps in evaluating the quality of MT engine by comparing the raw MT to the post edited version by a human translator.

3- Fuzzy Match

In translation memories, edit distance is the technique of finding strings that match a pattern approximately (rather than exactly). Translation memories provide suggestions to translators, and fuzzy matches are used to measure the effort made to improve those suggestions.