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Category: Translation Management Systems

TMS Final Mini-Portfolio

December 7, 2017 / / 0 Comments

Introduction

This portfolio is a compilation of a translation project done within a translation management system called SDL WorldServer by my team TMS Spice Girls in the course Translation Management Systems during the 2017 fall term, and three blog posts titled “Quality Models & QA”, “Translation Management Systems for Crowdsourcing” and “Tips for selecting the best TMS”. All of these support my comprehension of how to implement a translation project in a TMS, what features and functions a TMS should have to meet the needs of completing a translation project and my evaluation on the selection and adoption of a suitable TMS for a company.

Translation Project in SDL WorldServer

The translation project our team has completed in SDL WorldServer through this semester was to translate two content pages of marketing materials in the format of XML files from English to Simplified Chinese for our client King & Wood Mallesons Law Firm and the process included pre-translation setup, translation and QA.  The final project files that our team created when doing the project include a proposal, the source and target texts, pseudo translations and the presentation slides on lessons learned, and the project folder can be accessed via the hyperlink above. The project was done based on what we’ve learned over the semester, including how a TMS like SDL WorldServer operates in different aspects related to, for instance, finance, user accounts, QA models and translation. Moreover, the presentation slides also contain things our team think WorldServer should improve based on the challenges and problems we met during the project. This project gave me a clearer and more detailed picture of how to manage a translation project inside a TMS and what the workflow would be like.

Blog Posts

Each of the three blog posts explores a different aspect of translation management systems and refers to either a video conference or articles posted by experts in the translation and localization industry.

  • “Quality Models & QA”

Based on a video introducing MQM (Multidimensional Quality Metrics), the article explores the benefits of MQM, the reasons why it’s needed and how it might influence the use of TMSs.

  • “Translation Management Systems for Crowdsourcing”

With the reference of three articles, the blog post illustrates the definition of translation crowdsourcing, the differences between crowdsourced translation and traditional translation, the features a TMS might have to implement crowdsourcing and how crowdsourced translation should be managed.

  • “Tips for selecting the best TMS”

Based on four online articles, this blog post explains the things a company should take into consideration when selecting the best TMS from the points of view of both the client side and the vendor side. In addition, it elaborates the most important factor that I think a company should focus on when choosing TMSs, which is, the translators.

Tips for selecting the best TMS

December 6, 2017 / / 0 Comments

Source:

  1. “Eight Steps to a Successful TMS Roll-Out” by Andrew Lawless (Rockant/DigIT) http://rockant.com/wp-content/uploads/ubpfattach/eight-steps-to-a-successfull-tms-roll-out.pdf
  2. “Implementing a Translation Management System: 4 Things to Keep in Mind” by Camille Poudens (Freedman International) https://www.freedmaninternational.com/blog/blog/category/implementing-a-translation-management-tool
  3. “Choosing a TMS: Getting Started” by Yee Lam Cook and Viviana Bertinetto (Global Language Solutions) https://www.gala-global.org/publications/choosing-tms-getting-started
  4. “Shopping for a Translation Management System: How to Choose the Best for Your Company” (Sajan) http://www.sajan.com/shopping-for-a-translation-management-system-how-to-choose-the-best-for-your-company/

 

Selecting a suitable and effective translation management system is an important thing for both client companies and LSPs. For a company from the client side that wishes to find the best translation tools, it has several steps to go through before making the decision. Firstly, according to Brian McConnell in his article “Choosing The Best Translation Technology for Your Company”, the most valuable thing to do is to do some research and get itself familiar with the translation and localization industry to understand how this industry operates and what categories of products and services are. Second, evaluate the tools based on its own technology and process rather than on the needs of its translation agency. Third, involve bilingual staff in the localization and translation efforts since they are able to assist with translation and market expansion projects. And finally after filtering out some of the options, all it has to do is to test out the candidates and evaluate them based on the staff’s opinions in terms of their usability, workload reduction and output quality. Resources can now be shift into the solution that wins.

For the vendor side, there are much more factors to be taken into account during the selection of the best TMS.

The first thing to do before the search is to understand the current and future translation needs in the company. This includes evaluating the actual necessity of owning a TMS tool based on the projects to be managed, the project management needed (regarding the way the projects to be handled and the desired level of automation), finance tracking system and the requirement of integration and interoperability between systems. After having a big picture of the company’s blueprint, the next thing to do is to involve all the human resources in the process of selecting a TMS. All the different internal departments that will be affected by the decision should be taken into consideration since they will be the ones to implement the product. Moreover, vendors should also be involved as early as possible and they have the right to be notified of the change in advance. Research on the vendors’ major concerns and their opinions is significantly necessary to build constructive suggestions for choosing the right tool. Before implementing the tool, the company is supposed to think about the allocation of resources for setup, training, customization login creations and so on. Last but no least, test, test, and test again. But testing can be tricky. The core is to identify a team that works on the same project type, ask them to launch a small internal project to test the tool out and gain feedbacks.

For me, I couldn’t agree more that it is so necessary to consider the translators during the selection of a new tool. It aroused my consensus that “Some tools are far better for managers than for translators. The different editor interfaces and features might be great for PMs, but not for the people actually working with the copy”, especially for an external vendor. A good LSP is a one that also think about the vendors, asking them whether they are willing to learn new tools and delving into the way the tool works to make sure their life won’t be made hard because of it. Since vendors consists of one of the crucial part of the translation and localization process, they are key to the company’s success and whether they are happy with the chosen TMS matters. And that’s why when we started to look for volunteer vendors for our Localization Practicum projects, the first thing we asked on our survey form is: Are you interested in learning a new tool for your translation?

Translation Management Systems for Crowdsourcing

December 6, 2017 / / 0 Comments

Source:

  1. “Facebook Taps Users to Create Translated Versions of Site” by Michael Arrington, TechCrunch, January 21, 2008
  2. “Can Companies Obtain Free Professional Services through Crowdsourcing? ” by Adam Wooten, DeseretNews.com, February 18, 2011
  3. “People-powered Translation at Machine Speed” by Jessica Roland, MultiLingual, January 2014

 

With the development of technologies and the increased flow of information, crowdsourcing is gaining more popularity and has been adopted by many companies allowing them to improve their production capacity while lowering the costs at the same time. Crowdsourcing is also happening in the translation industry as well.

Translation crowdsourcing is the practice of obtaining translation services from a large group of people, usually multilingual users, especially from an online community. For example, Facebook has invited its multilingual users to translate phrases from the site pages that need to be translated. For me, there’s only a tiny difference between crowdsourced translation and volunteer translation, and that is, crowdsourced translation includes both paid and unpaid translation while volunteer translation is absolutely unpaid, even though the word “unpaid” is actually not accurate in the strict sense because it still costs money to manage the platform of crowdsourcing and the quality of translation.

Because of the difference between the forms of crowdsourced translation and traditional translation, these two practices have to be managed differently. First of all, translators in the traditional translation environment often use complicated CAT tools which can be expensive and hard to learn, but in crowdsourced translation environment, users should understand what to do and how to do it right way to ensure speed. In addition, traditional translation commonly has individual rates for each language while crowdsourced translation might have a single rate across languages per target quality level.

According to Jessica Roland in her article “People-powered translation at machine speed”, a TMS might have several certain features to facilitate crowdsourcing, including:

  • Streamlined and intuitive systems for ordering and translating
  • Reduced operations for translators and clients

And the technology should meet certain special needs, such as:

  • Having an automated quality checking process
  • Having a strong and flexible system so that it can handle a large crowd of translators working at the same time and the crowd can grow and shrink to accommodate various order volumes in different sizes
  • Having a highly automated translator acquisition system including online feeder channels and automated online testing

After reading the three articles, I think paid translation crowdsourcing can also be counted as crowdsourcing since it still reaches out to translators and will create the products with everyone’s efforts. To manage this kind of crowdsourcing, a TMS should also have systems that deal with payment. So it should support multiple currencies and regular translator payments via international payment methods such as Paypal and should have simple, transparent pricing and efficient payment systems for quotes and invoices.

I think one of the best things for translation crowdsourcing is that the crowd will often self-correct and manage QA on its own. Users tend to let us know which translations or translators they disapprove of. Facebook utilized this idea quite well and they let other users vote on the submissions by other translators or submit their own version rather than let their own internal QA people to do the job. Therefore, a good TMS to manage crowdsourced translation would also provide a platform for the crowd to evaluate each other’s work.

Quality Models & QA

December 6, 2017 / / 0 Comments

Source:

Video “2013-07 QTLaunchPad: MQM Version 2 and Software Infrastructure” by Arle Lommel: https://vimeo.com/71836764

 

The video illustrates the existing problems of human metrics and machine translation metrics respectively. There’s no consistency for human metrics that cover over 180 different issues to be checked. Because of the “One-size-fits all approaches”, human metrics are not flexible enough to handle the needs of different projects since, for example, perfect grammar may not matter that much in gist translation, and legal translation requires both accuracy and fluency. Also, human metrics are totally disconnected with MT evaluation which doesn’t help improving the MT quality.

For machine translation metrics, metrics like BLEU score don’t indicate what kinds of problems the translation result has, such as inconsistency of terminology and mistranslation, but only how much the result deviates from the reference materials. They also confuse different things including product quality (fluency, accuracy and verity), process and project.

MQM has multiple benefits. First of all, different hierarchical levels of issue types are created for different tasks. It is currently divided into four branches, namely, accuracy, fluency, verity, and design and follows a system of a core and extensions in which the core supports common issues while the extensions support additional needs and are suitable for some specific purposes. In addition, users can select task-specific metrics to check only what’s needed. So even though this is a quite complex model, people only have to use those parts they need.

For me, I think MQM will influence the design of the QA section in a TMS in some way. For instance, based on the multiple ways to use MQM illustrated by the lecturer, the QA function in a TMS can adopt the predefined MQM model but should also allow the users to add cores and extensions based on different scenarios. A great thing to do with the metrics would be specifying aspects to check in certain subject fields. A TMS can connect with the translation principles of certain industries and be updated anytime so that when the users select the subject field for a certain project, the common issues to check for that industry will automatically pop up, but of course it should allow the users to make changes. In this way, people will have a big picture of how others evaluate the translation for a certain industry and personalize the metrics based on individual projects.

That being so, I’m wondering whether those who created the MQM have a platform for people to share the experience of what different aspects they select to check for different projects and whether they have a way to collect all the information because I think those experience can really be a guidance for startup vendors and even for translation management systems to create their default or suggested QA sub-models based on the big MQM model.

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