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As noted in our post about automatic machine translation (MT) engine selection, identifying the right engine for your language pair and domain is not a straightforward choice. That is why machine translation auto-select features are being added to the Translation Management System (TMS) offerings, such as Memsource.
A specific use case worth exploring in this regard is MT for User Generated Content (UGC). Because of the speed with which UGC (comments, feedback, reviews) is being created and the corresponding costs of its professional translation, many organizations turn to MT.
Popular examples of such companies are Skype (in addition to text translation, Microsoft developed the Automatic Speech Recognition (ASR) for audio speech translation in Skype) and Facebook. The social network is aiming to solve the challenge of fine-tuning each system relating to a specific language pair, using neural machine translation (NMT) and benefiting from various contexts for translations.
MT is already a working solution for large volumes of UGC. Problems occur when users make typos or use slang, however. How does MT cope with the messy unstructured type of content?
One solution that tackles this issue is the technology developed by Language I/O. The company’s SaaS platform translates chats, emails, and other UGC instantaneously via MT. It takes into account the client's glossaries and TMs, selects the best MT engine output and then improves on the results using cultural intelligence and/or human linguists who compare machine translations post-facto to ensure that their MT Optimizer engine learns over time.
The solution is powered by Language I/O machine learning technology coupled with an MT aggregator and a proprietary glossary imposition layer. Because the integrated MT engines are constantly learning in their own right, the MT Optimizer needs to continuously improve its ability to select the best MT engine for each translation request based on:
- feedback from customer service reps in the customer relationship management (CRM) tool using a Language I/O CRM translation app
- feedback from customers who consume Language I/O translations
- edit distance data coming from translators using CAT and TMS tools integrated with TAUS DQF
This tech plugs into Salesforce, Oracle, and Zendesk – the CRM platforms where support agents already work. They are also providing their APIs so that anyone with UGC can use the service (not necessarily just customer service personnel).
