Machine Translation
Definition
Machine Translation leverages AI and neural networks to automatically convert text or speech between languages, enhancing global communication.
Use Cases
- Airbnb: Translate listings, reviews, and messages so hosts and guests can communicate across languages. — Airbnb has described using machine translation in its product to localize user-generated content and improve cross-language communication, integrating translation into the app experience with automated language detection and on-demand translation. (Improved usability for international travelers and hosts by reducing language barriers and increasing the amount of content accessible to users in their preferred language.)
- eBay: Translate product listings and item descriptions to support cross-border e-commerce. — eBay has publicly discussed applying machine translation to user-generated listing content so buyers can understand listings written in other languages, integrating translation into the marketplace experience. (Helps buyers discover and understand more inventory across regions, supporting cross-border trade and improving the shopping experience for international users.)
- Microsoft (Bing/Microsoft Translator): Real-time translation for web content and communication scenarios. — Microsoft operates a large-scale neural machine translation system (Microsoft Translator) used across products and exposed via Azure AI Translator APIs for developers to embed translation into apps and workflows. (Enables multilingual experiences at internet scale, reducing the need for manual translation for high-volume, fast-changing content.)
Provider Equivalents
- AWS: Amazon Translate
- Azure: Azure AI Translator
- GCP: Cloud Translation
- OCI: OCI Language (Translation)
Frequently Asked Questions
- What's the difference between Machine Translation and localization?
- Machine Translation converts text from one language to another automatically. Localization is broader: it adapts content for a specific region or culture (tone, units, currency, date formats, legal wording, images, and sometimes rewriting). A common workflow is: machine translation for speed, then human review/localization for customer-facing or high-risk content.
- When should I use Machine Translation?
- Use it when you need fast, scalable translation for large volumes of content, such as support tickets, chat messages, knowledge bases, product catalogs, user reviews, or internal documents. It’s especially useful when “good enough” translation is acceptable or when you can add human review for critical content. Avoid relying on it alone for legal, medical, safety, or brand-sensitive text without expert review.
- How much does Machine Translation cost?
- Most cloud translation APIs charge by the number of characters translated (and sometimes by document type or advanced features). Total cost depends on monthly character volume, number of languages, whether you translate both directions (incoming + outgoing), and whether you use add-ons like custom models, glossary/terminology features, or document translation. To estimate, calculate: (characters per message or page) × (messages/pages per month) × (number of translation passes).
Category: software
Difficulty: intermediate
Related Terms
See Also