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Recurrent neural network language models (RNNLMs) have been successfully applied in a variety of language processing applications ranging from speech recognition to machine translation. They can fight the curse of dimensionality by learning a distributed representation (word vector). The components of these vectors measure the co-occurrence of the word with context features over a corpus. However,...
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