dialog context c:前k-1个utterances,conversational floor(1或0),meta features(topic)
latent variable z: capture distribution of valid responses
x: response utterance
y:linguistic features(knowledge-guided CVAE)
p(z|c):prior network
p(x|z,c): response decoder,用q(x|z,c) recognition network来模拟
生成过程:sample z, generate x如图c所示
训练过程,如图b所示,通过max L目标函数得到q p的两个参数,从而得到z的分布。再由z生成response