• DocumentCode
    2363531
  • Title

    Automatic speech segmentation using neural tree networks

  • Author

    Sharma, Manish ; Mammone, Richard

  • Author_Institution
    CAIP Center, Rutgers Univ., Piscataway, NJ, USA
  • fYear
    1995
  • fDate
    31 Aug-2 Sep 1995
  • Firstpage
    282
  • Lastpage
    290
  • Abstract
    Segmentation of speech into sub-word acoustic units using neural tree networks (NTNs) is presented. NTN is a hierarchical classifier that combines the properties of both decision trees and feedforward neural networks. The number of sub-word acoustic units in a given speech segment may or may not be known to the segmentation algorithm. Both these varieties of speech segmentation problems are addressed. The performance of the speech segmentation algorithm using NTN is compared to that obtained using hidden Markov models (HMMs) and dynamic programming-based approach proposed elsewhere
  • Keywords
    decision theory; feedforward neural nets; speech processing; speech recognition; trees (mathematics); decision trees; feedforward neural networks; hierarchical classifier; neural tree networks; speech recognition; speech segmentation; Algorithm design and analysis; Classification tree analysis; Decision trees; Feedforward neural networks; Feedforward systems; Hidden Markov models; Neural networks; Speech processing; Speech recognition; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing [1995] V. Proceedings of the 1995 IEEE Workshop
  • Conference_Location
    Cambridge, MA
  • Print_ISBN
    0-7803-2739-X
  • Type

    conf

  • DOI
    10.1109/NNSP.1995.514902
  • Filename
    514902