Content in Translation
Accessing new markets the right way
AGI v1.0 Will Be Harness + Skills
Consider the trajectory of LLMs so far. Starting in Google’s translation research departments, following on from their groundbreaking neural network models, transformers were first and foremost a “language” model. They have grown to be able to convince people of their utility, much like the market stall owner would do pre-2000s, holding groups of up to 50 people in awe because of their fast talking, confidence and skill demoing whatever they were selling. The same works on shopping channels and more recently Youtube. Speak fast and confidently, cut all the dead air, and you got yourself the makings of a popular channel.
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Batch Audio Transcription at Scale
Your organization has 500 audio recordings that need transcription. Maybe they’re customer calls for analysis, training recordings for localization, meeting recordings for documentation, or podcast episodes for subtitling.
Transcribing them one at a time would take weeks. And the real work starts after transcription: translation, subtitling, analysis, or whatever downstream process needs text from audio.
Batch processing makes audio transcription practical at scale.
The scale problem
Modern ASR (automatic speech recognition) processes audio in real-time or faster. A 10-minute recording transcribes in under 10 minutes. One recording is trivial.
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Content Discovery for Global Markets: Find What Works, Then Translate
Creating content from scratch for each market is the expensive approach to global content strategy. The alternative: find content that’s already proving itself in other markets and adapt it.
This isn’t copying. It’s market intelligence applied to content creation.
The content creation treadmill
Typical multilingual content approach: create content in the primary market, then translate it for secondary markets.
Problems with this approach:
- Primary market content may not resonate in secondary markets
- Secondary markets get translated versions rather than market-appropriate content
- Content strategy is defined by one market’s needs
- Missed opportunities in what’s working elsewhere
Organizations spend heavily creating original content, then assume that content will work everywhere once translated. Sometimes it does. Often it doesn’t.
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Transcreation vs Translation: When Direct Isn't Good Enough
Nike’s “Just Do It” doesn’t translate. Not because it’s hard to express in other languages, but because a literal translation wouldn’t carry the cultural weight and emotional resonance that made the slogan iconic.
This is the transcreation problem: some content needs more than accurate translation to work in a new market.
The translation-transcreation spectrum
Content exists on a spectrum from highly translatable to requiring complete recreation:
Highly translatable: Technical documentation, legal contracts, scientific papers. Accuracy matters most. Creative interpretation is unwelcome.
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Brand Voice Across Languages: Maintaining Identity in Every Market
Brands invest heavily in voice. Workshops define personality. Style guides document preferences. Writers train on the desired tone. The resulting voice becomes part of brand equity—recognizable, differentiated, valued.
Then translation happens, and the voice disappears.
Where brand voice gets lost
Translation focuses on meaning transfer. Voice is conveyed through choices that don’t directly carry meaning: word selection among synonyms, sentence rhythm, punctuation style, register, formality level.
A translator choosing between “utilize” and “use” picks based on source text and target language conventions. The brand preference for plain language over jargon isn’t visible to them. So “use” becomes “utilizar” even when the brand voice calls for simpler terms.
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SCORM Localization: The E-Learning Translation Gap
E-learning localization looks simple on the surface: extract the text, translate it, put it back. In practice, SCORM packages are complex containers with dozens of content types, each requiring different handling.
Organizations discover this when their translated courses don’t work—quizzes broken, interactions failing, audio unchanged, images still showing source language text.
What’s actually in a SCORM package
A SCORM package (SCORM 1.2 or SCORM 2004) typically contains:
HTML content pages. The main learning content, often with embedded JavaScript for interactions.
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Connect Your TMS Without Switching: The Connector Approach
Your organization uses Phrase. Or Lokalise. Or MemoQ. Or one of dozens of other translation management systems. The workflows are established, teams are trained, data lives there.
Now you need a capability your TMS doesn’t have—advanced AI translation, cross-lingual QA, video dubbing. Do you switch platforms?
Switching is painful. Connectors offer an alternative.
The platform switch problem
Changing TMS platforms involves:
Data migration. Translation memories, termbases, project history—all needs extraction and import. TM quality often degrades in translation between formats.
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