(no title)
sapphireblue | 9 years ago
Given modern deep learning conversation models it is already possible to recreate some basic patterns of human dialogue with a recurrent neural network trained on a large corpus (see Google's "A Neural Conversational Model" paper and someone's implementation of it: https://github.com/macournoyer/neuralconvo ).
It would be interesting to experiment with it and see, just how far can we push this modeling approach? How much data is needed? Is it possible to train the model on a huge corpus of human dialogues, and then to finetune it on small amount of data from one specific person?
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