Topic indexing of spoken documents based on optimized N-best approach

@article{Zhang2009TopicIO,
  title={Topic indexing of spoken documents based on optimized N-best approach},
  author={Lei Zhang and Jingxin Chang and Xuezhi Xiang and Xiaosen Feng},
  journal={2009 IEEE International Conference on Intelligent Computing and Intelligent Systems},
  year={2009},
  volume={4},
  pages={302-305}
}
For topic indexing of spoken documents, the word error rate is hopefully decreased instead of the whole sentence error rate, so the center hypothesis among the N-best results is selected as the final output in speech recognition system. Then all spoken documents can be represented as vectors with high dimensions in vector space model, which can be combined… CONTINUE READING