chatbot-rnn
A toy chatbot powered by deep learning and trained on data from Reddit
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Sequence-to-sequence neural network models for generation of conversational responses tend to generate safe, commonplace responses (e.g., "I don't know") regardless of the input. We suggest that the traditional objective function, i.e., the likelihood of output (response) given input (message) is unsuited to response generation tasks. Instead we propose using Maximum Mutual Information (MMI) as the objective function in neural models. Experimental results demonstrate that the proposed MMI models produce more diverse, interesting, and appropriate responses, yielding substantive gains in BLEU scores on two conversational datasets and in human evaluations.
READ FULL TEXTA toy chatbot powered by deep learning and trained on data from Reddit
Please aware that the data provided is already outdated. Sample data would be uploaded for users to test on their own.
This code is taken directly from https://github.com/pender/chatbot-rnn. Customized to work with python 3.5 and tensorflow 1.0.
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