A DNN-HMM Approach to Story Segmentation

  title={A DNN-HMM Approach to Story Segmentation},
  author={Jia Yu and Xiong Xiao and Lei Xie and Chng Eng Siong and Haizhou Li},
Hidden Markov model (HMM) is one of the popular techniques for story segmentation, where hidden Markov states represent the topics, and the emission distributions of n-gram language model (LM) are dependent on the states. Given a text document, a Viterbi decoder finds the hidden story sequence, with a change of topic indicating a story boundary. In this paper, we propose a discriminative approach to story boundary detection. In the HMM framework, we use deep neural network (DNN) to estimate the… CONTINUE READING


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