Two Little-Known Ways AI Improves Translation Management
When considering artificial intelligence in terms of language services, we tend to think only of the linguistic applications of AI - which aren’t inconsiderable. Powerful AI is capable of breaking down a source document into its linguistic parts, translating those portions, then re-assembling that information in the target language at great speed and high quality. There are, however, plenty of other ways that AI can improve the translation process. Let’s take a look at two:
Typically, file analysis is done manually by translators through Computer-Assisted Translation (CAT) tools, helping them understand wordcounts, estimated costs, and extract key terms. This time-consuming process requires the translator to transfer files multiple times, leading to a higher margin of error, potential data loss, and long wait times even for something as simple as a price quote.
The integration of AI streamlines this process because it supports a variety of file types (including scanned documents), and automatically detects the source text’s language, then leverages it against cloud-based translation databases to give you a real-time price quote. Rather than sending a project and waiting anywhere from days to weeks for a response, powerful algorithms analyze your document and have relevant information ready to report to you in mere seconds.
Provisioning is a time-intensive portion of the translation process done by project managers, who must manually assign translation projects to individual translators who may or may not accept. When a large number of languages is involved, this process becomes even more time and resource intensive, because it requires a greater amount of communication between a greater number of people. Even when the manager does their part in reaching out to the right parties, there is no guarantee that the project will be picked up in a timely manner by qualified linguists. As a result, timeframes are largely out of the client’s control.
The introduction of artificial intelligence into translation provisioning has had a profound effect on the efficiency of the process as a whole. Artificial intelligence decreases the workload and strain on project managers, and increases quality, consistency, and timeliness of translations by streamlining the translation workflow. Once a project is received, complex algorithms extract the source material into multiple segments or “jobs” depending on the word count and deadline provided by the client. The TMS AI then filters all available translators according to expertise and ratings, and assigns them jobs accordingly. Consistency and accuracy are guaranteed (despite the number of translators) by one centralized Dynamic Terminology System which the assigned translators are required to use. Then, the completed segments are synthesized into a final, high-quality document.