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GENERATING DIALOGUE RESPONSES IN END-TO-END DIALOGUE SYSTEMS UTILIZING A CONTEXT-DEPENDENT ADDITIVE RECURRENT NEURAL NETWORK
GENERATING DIALOGUE RESPONSES IN END-TO-END DIALOGUE SYSTEMS UTILIZING A CONTEXT-DEPENDENT ADDITIVE RECURRENT NEURAL NETWORK
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机译:利用上下文相关的递归神经网络在端到端对话系统中生成对话响应
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摘要
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating dialogue responses based on received utterances utilizing an independent gate context-dependent additive recurrent neural network. For example, the disclosed systems can utilize a neural network model to generate a dialogue history vector based on received utterances and can use the dialogue history vector to generate a dialogue response. The independent gate context-dependent additive recurrent neural network can remove local context to reduce computation complexity and allow for gates at all time steps to be computed in parallel. The independent gate context-dependent additive recurrent neural network maintains the sequential nature of a recurrent neural network using the hidden vector output.
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