• DocumentCode
    3141672
  • Title

    ASR post-processing correction based on NER and pronunciation primitive

  • Author

    Jun, Jiang ; Lei, Li

  • Author_Institution
    Intell. Technol. Res. Center, Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2011
  • fDate
    27-29 Nov. 2011
  • Firstpage
    126
  • Lastpage
    131
  • Abstract
    In dealing with robustness of specific areas,such as automatic speech recognition (ASR).this paper proposes some new ideas. The idea of using named entity recognition(NER), which is domain-specific is based on the conditional random field(CRF).NE are used to establish the context, leading the speech recognition process´ pronunciation element into the post-treatment of speech recognition, Speech recognition results are represented with pronunciation primitive characters. And based on the improved dynamic edit distance we find the appropriate entity context, and then according to the context of the entity we try to optimize the recognition results.
  • Keywords
    speech recognition; ASR post-processing correction; automatic speech recognition; conditional random field; dynamic edit distance; entity context; named entity recognition; pronunciation primitive; Accuracy; Biological system modeling; Bismuth; Manuals; Robustness; Speech recognition; conditional random field; entity context; improved dynamic edit distance; named entity recognition; pronunciation primitive;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing andKnowledge Engineering (NLP-KE), 2011 7th International Conference on
  • Conference_Location
    Tokushima
  • Print_ISBN
    978-1-61284-729-0
  • Type

    conf

  • DOI
    10.1109/NLPKE.2011.6138180
  • Filename
    6138180