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textstyletransferdata's Introduction

Text Style Transfer Data

Evaluation

Evaluation tool is in eval

Preprocess

  • put glove embedding in eval/word_emb.
  • Please follow run1.sh to put test data.
  • The results of converting test data to style 0 is put in style0.txt and style 1 respectively.
  • test1 test2 test3 for different mode (autoencoder, style embedding. multi decoder).

Transfer Strength (Classifier)

$ python classifier data        # process data of classifier
$ python classifier train       # train classifier
$ python classifier test test1  # test classifier
                                # test1 is the test result dir
                                # results in test1/embedding/style0_classification.txt ...

Content reservation

$cd eval
$python emb_test.py test1   # test1 is the test result dir
                           # results in test1/embedding/style0_semantics.txt ...

Finally, run python eval.py to show results collection.

Example:

dir_name model_type      transfer_strength content_reservation mixture
================================================================================
test1     embedding8 		0.267 		0.943880306299 	0.208126303212
test1 	embedding4 		0.485 		0.915346000157 	0.317023657029
test1 	embedding 		0.593 		0.896598659955 	0.356930373024
.................

Acknowledgment

Thanks for Fangfang Zhang and Yixin Zhang for helping compose data.

textstyletransferdata's People

Contributors

fuzhenxin avatar yaolili avatar

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