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Generating Sequences With Recurrent Neural Networks

Generating Sequences with Recurrent Neural Networks Alex Graves [ ] 5 Jun 2014. Department of Computer Science University of Toronto Abstract This paper shows how Long Short-term Memory Recurrent Neural net- works can be used to generate complex Sequences with long-range struc- ture, simply by predicting one data point at a time. The approach is demonstrated for text (where the data are discrete) and online handwrit- ing (where the data are real-valued). It is then extended to handwriting synthesis by allowing the network to condition its predictions on a text sequence .

Recurrent Neural Networks Alex Graves Department of Computer Science University of Toronto graves@cs.toronto.edu Abstract This paper shows how Long Short-term Memory recurrent neural net-works can be used to generate complex sequences with long-range struc-ture, simply by predicting one data point at a time. The approach is

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