Communications of the ACM
How Neural Networks Are Transforming the World of Translation
Translation software will become a genuinely useful business tool, thanks to machine learning.
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Imperial College London professor Erol Gelenbe says artificial neural networks can ease language translation by executing a three-step process.
The process includes word translations, syntax mapping, and contextual translation, which Gelenbe, recipient of the 2008 ACM SIGMETRICS Achievement Award, says the neural networks can achieve by storing and matching patterns.
A key element of the translation process is long short-term memories (LSTMs), which support machine learning and can learn from experience. Swiss Dalle Molle Institute for Artificial Intelligence president Jurgen Schmidhuber expects LSTM recurrent neural networks to eventually enable "end-to-end video-based speech recognition and translation, including lip-reading and face animation."
Meanwhile, Google Brain recently announced its researchers are using neural networks to improve speech-to-text translation.
Microsoft Research's Rick Rashid says the creation and deployment of deep-learning neural networks by his company's researchers has significantly reduced word error rates in transcribed translations, which he notes could be useful to international business dealings, and have a major effect on cross-industry learning.
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