Abstract: Aspects of the present disclosure provide accelerated transfer learning for machine learning models, such as neural networks, as a service. In doing so, the aspects disclosed herein decouple the conversion process for use of machine learning models from deployment of the models in a production environment through the creation of one or more common generic models that execute on a hardware accelerator, such as a FPGA. Additional aspects of the disclosure relate to the creation of an accelerated machine learning model. The accelerated machine learning model is created by identifying common portions of a machine learning model that can be leveraged by a plurality of different machine learning models. Still further aspects of the disclosure relate to training scenario specific machine learning models for use with an accelerated machine learning model.

Abstract: In order to achieve improvement of the accuracy and speed of a conversion of source language elements to target language elements a machine translation system is provided with context and linguistic processing comprising a dictionary storage 100, linguistic analysis storage 114, transfer rule storage 116 and a context storage 130, wherein selecting means 118 determines an order of selection among transfer rules to be executed to obtain target language elements from linguistic processing and target language elements from context processing. The correlation between language elements and context elements is obtained using a neural network.