In this session, we will discuss an alternative solution to the current DQF API in which translated data segments remain on enterprise servers. TAUS is planning on providing an open specification of methods to facilitate the aggregation of data on the enterprise side. The benefit of this solution is that the actual translated segments and other sensitive data are not shared. This is more economic and it makes DQF more attractive to enterprises that are restricted in their sharing of data with a third party. Participants will be invited to share their thoughts and provide feedback on this new solution. Session leader: Vincent Gadani (Microsoft) Panelists: Fred Tuinstra (Lionbridge), Paola Valli (TAUS)

1. MICROSOFT AND DQF

2. WHY DO WE NEED A BENCHMARK?
• Quality of a translation is a complex balance of multiple factors
• Quality of your recycling workflow
• Quality of your translation model (MT only MTPE or HT)
• Quality of your translation team
• Quality of your processes and communication
• And many more...
• We already evaluate our quality internally, mostly aligned to the DQF model.
• What’s missing is an industry reference point. That can tell us, whether our workflow is efficient or not.
• It can not be achieved without sharing our own data with the industry.

3. WHAT COULD WE DO WITH SUCH A
BENCHMARK?
• Identify how well our overall translation system perform
• Evaluate efficiency of different translation model
• Identify areas where we fall short and investigate how to improve.
• Think:
• Different priority
• Difference perspectives

4. MS CONSTRAINTS
• MS developed and maintained TMS
• Continuous translation workflow. There is no concept of project.
• A lot of data going through the system.
• Many unreleased and unannounced features
• These constraints are shared by many enterprise customers for whom the current
implementation of DQF is not practical.
• We need a different set of DQF API to address these constraints and be able to share.