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From Feedforward to Recurrent LSTM Neural Networks for Language Modeling

Audio, Speech, and Language Processing, IEEE/ACM Transactions  , no. 3 (2015): 517-529

Cited by: 362|Views154
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Abstract

Language models have traditionally been estimated based on relative frequencies, using count statistics that can be extracted from huge amounts of text data. More recently, it has been found that neural networks are particularly powerful at estimating probability distributions over word sequences, giving substantial improvements over stat...More

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