Machine translation (MT) solutions have come a long way in producing quality translation output that meets human quality acceptance. Like any other NLP solution, modern deep-learning based MT engines require large volumes of translated texts to build the translation intelligence.
A machine translation engine is only useful if it is trained with the right type of translated training data for the right use case. For example, MT solutions trained for the healthcare industry, perform poorly in legal sectors. Public MT solutions offered by large internet platforms are trained on publicly available data across the internet and do not provide focused quality across a specific vertical. Hybrid Lynx develops the right corpus for your use case within your industry and target market.