AppTek, a provider of Artificial Intelligence (AI) and Machine Learning (ML) for Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), Natural Language Processing / Understanding (NLP/U) and Text-to-Speech (TTS) technologies, announced the release of its new neural machine translation system that incorporates metadata as inputs used to customize the MT output and empower localization professionals with more accurate user-influenced machine translations. Additionally, the company expanded its core machine translation platform to support hundreds of language and dialect pairs.
Traditionally, enterprises would need to train, deploy and maintain multiple MT systems to account for translation tasks that differ in aspects such as language, dialect, domain, topic, and more, at the risk of high deployment costs and overfitting models.
With AppTek’s new metadata informed NMT platform, enterprise customers can now access a single NMT system with multi-domain, multi-genre, multi-dialect content which increases the quality and adaptability of the system. By feeding additional metadata into the system, they gain more control of the MT output and can enable translators to simply “flip the switch” to the desired customized translation through relevant functionality in the user interface of the editing tools professionals work with.