![]() ![]() Torch can take advantage of GPU acceleration, which means the training process for OpenNMT models can be sped up a great deal on any GPU-equipped system. After training OpenNMT on this data, the user can then deploy the resulting model and use it to translate texts. The user prepares a body of data that represents the two language pairs to be translated-typically the same text in both languages as translated by a human translator. OpenNMT, which uses the Lua language to interface with Torch, works like other products in its class. Ideally, OpenNMT could serve as an open alternative to closed-source projects like Google Translate, which recently received a major neural-network makeover to improve the quality of its translation.īut the algorithms aren't the hard part it’s coming up with good sources of data to support the translation process-which is where Google and the other cloud giants that provide machine translation as a service have the edge. It runs on the Torch scientific computing framework, which is also used by Facebook for its machine learning projects. ![]() ![]() Open Source Neural Machine Translation ( OpenNMT) merges work from researchers at Harvard with contributions from long-time machine-translation software creator Systran. Researchers have released an open source neural network system for performing language translations that could be an alternative to proprietary, black-box translation services.
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