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S3E9 Smart Strategies for Saving Costs with Machine Translation and Going Global with Lisa Zarfl

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Manage episode 338291824 series 2891683
Inhalt bereitgestellt von Zohra Mutabanna. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Zohra Mutabanna oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Lisa Zarfl comes from the beautiful city of Graz, Austria. I met Lisa at a conference, and her presentation on machine translations inspired me to bring her on the show.
In this latest episode, we talk about all things translation. More specifically, machine translation (MT) and how it can help a business reach a global audience while saving costs. We talk about how technical writers can help the company save costs upfront with the translation before they are deep into the process. Tune in right away as Lisa has all the nuggets for you.
Some questions we do a deep dive into:

  • What is machine translation (MT)?
  • What does the process for MT look like?
  • Is MT based on artificial intelligence?
  • Will MT replace the need for human translators? If not, why?
  • How does an LSP (Language Service Provider) discern which type of content is best suited for MT?
  • What is the difference between internalization and localization?
  • What are the top 3 things that technical writers need to do before they consider translation for their content?

Guest Bio
In Lisa's own words..
My name is Lisa Zarfl. I’m a project manager and in-house translator at MadTranslations based in Graz/Austria. I have several years of experience in the translation industry, specifically in managing the translation of MadCap Flare projects. My job allows me to follow my passion by combining the technological aspects of documentation with the demands of multilingual environments.
You can connect with Lisa on LinkedIn.
Audio Engineer - RJ Basilio

  continue reading

49 Episoden

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iconTeilen
 
Manage episode 338291824 series 2891683
Inhalt bereitgestellt von Zohra Mutabanna. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Zohra Mutabanna oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Lisa Zarfl comes from the beautiful city of Graz, Austria. I met Lisa at a conference, and her presentation on machine translations inspired me to bring her on the show.
In this latest episode, we talk about all things translation. More specifically, machine translation (MT) and how it can help a business reach a global audience while saving costs. We talk about how technical writers can help the company save costs upfront with the translation before they are deep into the process. Tune in right away as Lisa has all the nuggets for you.
Some questions we do a deep dive into:

  • What is machine translation (MT)?
  • What does the process for MT look like?
  • Is MT based on artificial intelligence?
  • Will MT replace the need for human translators? If not, why?
  • How does an LSP (Language Service Provider) discern which type of content is best suited for MT?
  • What is the difference between internalization and localization?
  • What are the top 3 things that technical writers need to do before they consider translation for their content?

Guest Bio
In Lisa's own words..
My name is Lisa Zarfl. I’m a project manager and in-house translator at MadTranslations based in Graz/Austria. I have several years of experience in the translation industry, specifically in managing the translation of MadCap Flare projects. My job allows me to follow my passion by combining the technological aspects of documentation with the demands of multilingual environments.
You can connect with Lisa on LinkedIn.
Audio Engineer - RJ Basilio

  continue reading

49 Episoden

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