8,838 registrants

ProZ.com's 2014 virtual conference for International Translation Day

Sep 30, 2014



Presentation

How Translators Can Assess PEMT Opportunities

You must log in before you can access most features of this event.

Schedule:This session ended at 20:00
Description:While most translators think that MT is MT and that Google is representative of what MT is capable of, there are good reasons to question this assumption, and better understand how MT is used in professional settings. In actual fact, the quality of MT can vary as dramatically as human translators of various levels of competence can vary. PEMT experiences can vary and while we often hear about the bad experiences we do not hear as much about good experiences. Each MT engine is unique and translators can learn to assess key characteristics to understand whether an MT opportunity is worth engaging or not.

This session will provide an overview of different kinds of MT that a translator may come upon in professional settings, and what the general implications of these differences are in terms of the translator experience of PEMT work. It will also provide some key guidelines on what to look for to ensure positive PEMT experiences. Additionally it will cover:
  • How to understand the MT Output Quality and implications for PEMT work difficulty
  • Key Metrics Used by MT developers
  • Performance and Compensation Implications
  • Developing Win-Win Scenarios
  • PEMT Training
  • Collaboration & Feedback Mechanisms
Language(s):أنجليزي
Speakers:Kirti Vashee
Kirti Vashee is VP of Enterprise Translation sales for Asia Online. He is a seasoned IT sales and marketing executive and statistical machine translation (SMT) enthusiast who was previously responsible for the worldwide business development strategy at Language Weaver.

He has long-term software industry experience (EMC, Legato, Dow Jones, Lotus) and has been involved in building and managing sales and support operations in Europe and Asia for several software companies.

He is the moderator of the Automated Language Translation group with ovber 4,000 members in LinkedIn and is active on Twitter (@kvashee) and the blogosphere on MT (kv-emptypages.blogspot.com) and translation related issues. He received his formal education in South Africa, India and the United States.

You must log in before you can access most features of this event.

On-demand content



Discuss this session