Localization Tips and Product Updates

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Being a developer you understand that to grow you need to be always learning, whether from books, visiting conferences, or reading articles like this one. Among the new essential skills, you should be acquiring right now is rightfully placed the ability to build software that supports localization.

The more people are translating your project, the less time it takes to receive results, no one can doubt that. But there’s no guarantee that translations made by several people will be consistent in tone of voice, wording, and terminology usage. A glossary is one of the resources that should be added to help your translators understand the key terminology and how it should be translated. In this article, we’ll show you how a termbase can improve your localization process, then explain how to build and translate a glossary. Storing your glossary in your localization platform is a great way to enhance collaboration between everyone involved in the project.

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import { Icon } from "astro-icon/components"; We gladly introduce the improved Messages that are now Conversations. Whether you are a project owner, manager, or translator you can easily contact others within Crowdin. Use Conversations to discuss project reports, decide who should create tasks or upload new files, talk to vendors and more.

Setapp is a subscription-based service for Mac applications created by MacPaw Inc. in 2016. It provides access to a growing collection of Mac software from different developers for a fixed monthly fee. MacPaw company already had an experience of localization with their other product CleanMyMac. That was localized into 3 languages and the experience proved to be successful as the company received a substantial rise in the user attraction and retention rates.

This fall, we released a new beta feature — Auto-substitution, which is now successfully out of beta. The main purpose of Auto-substitution is to increase the benefit of using the Translation Memory (TM) by suggesting translations with a higher similarity match. The feature recognizes non-translatable elements (such as tags, HTML entities, placeholders, numbers and more) in translations suggested by TM and if they differ from the ones in the source string feature replaces them.