• Corpus ID: 35167190

Recurrent Neural Network Structured Output Prediction for Spoken Language Understanding

@inproceedings{Liu2015RecurrentNN,
  title={Recurrent Neural Network Structured Output Prediction for Spoken Language Understanding},
  author={Bing Liu and Ian R. Lane},
  year={2015}
}
Recurrent Neural Networks (RNNs) have been widely used for sequence modeling due to their strong capabilities in modeling temporal dependencies. In this work, we study and evaluate the effectiveness of using RNNs for slot filling, a key task in Spoken Language Understanding (SLU), with special focus on modeling label sequence dependencies. Recent work on slot filling using RNNs did not model label sequence dependencies explicitly. We propose to introduce label dependencies in model training by… 

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