Building Multilingual Customer Support: Lessons from Real-Time Speech Translation
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When we started building real-time speech translation for PolyTalk, we thought the hardest part would be translation. It wasn't. The real challenge was keeping conversations natural. Supporting multilingual customer support sounds simple at first. Convert speech into text, translate it, generate speech in another language, and play it back. Plenty of AI models can handle each of those tasks individually. The difficult part is making all of them work together fast enough that two people can have…
1Key Takeaways
- When we started building real-time speech translation for PolyTalk, we thought the hardest part would be translation.
- The real challenge was keeping conversations natural.
- Supporting multilingual customer support sounds simple at first.
- Convert speech into text, translate it, generate speech in another language, and play it back.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that when we started building real-time speech translation for PolyTalk, we thought the hardest part would be translation.
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