  Recurrent Neural Networks (RNN), particularly Long Short Term Memory (LSTM)
RNNs, are a popular and very successful method for learning and generating
sequences. However, current generative RNN techniques do not allow real-time
interactive control of the sequence generation process, thus aren't well suited
for live creative expression. We propose a method of real-time continuous
control and 'steering' of sequence generation using an ensemble of RNNs and
dynamically altering the mixture weights of the models. We demonstrate the
method using character based LSTM networks and a gestural interface allowing
users to 'conduct' the generation of text.
