Vivi-poem-generation

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薇薇:会写诗的机器人

成员:王东,王琪鑫,骆天一,张纪袁,冯洋

vivi 3.0 (on going)

目标

  • Transfer modern sentences to poems
  • Utilize extra knowledge to boost innovation
  • Reinforcement learning to improve quality


vivi 2.0

基本方法

  • Tensorflow 实现
  • Attention-based LSTM/GRU S2S
  • Sampling words as input to generate the present sentence
  • Memory augmentation (global and local)
  • Local attention for theme (+)
  • Local attention on previous generation, with couplet assignment (line number?) (+)
  • N-best decoding (+)

实现细节

  • Rythms with less characters removed
  • Characters seldom used as rhythms words are removed
  • Characters that are low-frequency are removed

特性

  • 训练基础模型,用memory实现精细创新
  • 用memory可实现风格、体例转换
  • 用Local attention可实现人为指导创作(+)
  • 可实现律诗中的对仗

测试结果

论文

vivi 1.0

基本方法

  • Theano 实现
  • 基于sequence-to-sequence的LSTM/GRU模型, 运用Attention 机制。
  • 输入为一首诗的第一句,输出为后面所有句子
  • 预训练word vectors,用多种体例古文结合在一起训练
  • 生成时可对用户输入进行扩展


测试结果

论文


文章

薇薇的故事