IDEAS home Printed from https://ideas.repec.org/a/igg/japuc0/v9y2017i2p55-64.html
   My bibliography  Save this article

Feedback-Driven Refinement of Mandarin Speech Recognition Result based on Lattice Modification and Rescoring

Author

Listed:
  • Xiangdong Wang

    (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)

  • Yang Yang

    (Jiangsu Enterprise Information Operation Center, China Telecom Corporation Limited, Nanjing, China)

  • Hong Liu

    (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)

  • Yueliang Qian

    (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)

  • Duan Jia

    (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)

Abstract

In real world applications of speech recognition, recognition errors are inevitable, and manual correction is necessary. This paper presents an approach for the refinement of Mandarin speech recognition result by exploiting user feedback. An interface incorporating character-based candidate lists and feedback-driven updating of the candidate lists is introduced. For dynamic updating of candidate lists, a novel method based on lattice modification and rescoring is proposed. By adding words with similar pronunciations to the candidates next to the corrected character into the lattice and then performing rescoring on the modified lattice, the proposed method can improve the accuracy of the candidate lists even if the correct characters are not in the original lattice, with much lower computational cost than that of the speech re-recognition methods. Experimental results show that the proposed method can reduce 24.03% of user inputs and improve average candidate rank by 25.31%.

Suggested Citation

  • Xiangdong Wang & Yang Yang & Hong Liu & Yueliang Qian & Duan Jia, 2017. "Feedback-Driven Refinement of Mandarin Speech Recognition Result based on Lattice Modification and Rescoring," International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), IGI Global, vol. 9(2), pages 55-64, April.
    • Handle: RePEc:igg:japuc0:v:9:y:2017:i:2:p:55-64
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAPUC.2017040104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:japuc0:v:9:y:2017:i:2:p:55-64. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.