Labeled Data Generation with Encoder-Decoder LSTM for Semantic Slot Filling

  title={Labeled Data Generation with Encoder-Decoder LSTM for Semantic Slot Filling},
  author={Gakuto Kurata and Bing Xiang and Bowen Zhou},
To train a model for semantic slot filling, manually labeled data in which each word is annotated with a semantic slot label is necessary while manually preparing such data is costly. Starting from a small amount of manually labeled data, we propose a method to generate the labeled data with using the encoderdecoder LSTM. We first train the encoder-decoder LSTM that accepts and generates the same manually labeled data. Then, to generate a wide variety of labeled data, we add perturbations to… CONTINUE READING


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