CGMH is a sampling based model for constrained sentence generation, which can be used in keyword-to-sentence generation, paraphrase, sentence correction and many other tasks.

• Running example for parahrase: (All rejected proposal is omitted)
  what movie do you like most . ->
  which movie do you like most . (replace what with which) ->
  which movie do you like . (delete most) ->
  which movie do you like best . (insert best) ->
  which movie do you think best . (replace like with think) ->
  which movie do you think the best . (insert the) ->
  which movie do you think is the best . (insert is)

• Running example for sentence correction: in the word oil price very high right now . ->
  in the word , oil price very high right now . (insert ,) ->
  in the word , oil prices very high right now . (replace price with prices) ->
  in the word , oil prices are very high right now . (insert are)

• Extra Examples for sentence correction:
  origin: even if we are failed , we have to try to get a new things .->
  generated: even if we are failing , we have to try to get some new things .

  origin: in the word oil price very high right now .->
  generated: in the word , oil prices are very high right now .

  origin: the reason these problem occurs is also becayse of the exam .->
  generated: the reason these problems occur is also because of the exam .

• python

  • ==2.7

• TensorFlow

  • == 1.3.0

• python packages

  • numpy
  • pickle
  • Rake
  • zPar
  • skipthoughts

• word embedding

  • If you want to try using word embedding for paraphrase, you should download or train a word embedding first and place it at config.emb_path.

• Training language models

  • For each task, first train a backward and a language model:
    set mode='forward' and mode='backward' in config.py successively.
    run crrection.py / paraphrase.py / key-gen.py to train each model

• Generation

  • For generating new sample for each tasks:
    set mode='use' and choose proper parameter in config.py.
    run crrection.py / paraphrase.py / key-gen.py to sample.
    outputs are in output.