• DocumentCode
    1725954
  • Title

    Temporal information in tone recognition

  • Author

    Lin, Payton ; Syu-Siang Wang ; Yu Tsao

  • Author_Institution
    Res. Center for Inf. Technol. Innovation, Taipei, Taiwan
  • fYear
    2015
  • Firstpage
    326
  • Lastpage
    327
  • Abstract
    Traditionally, only five components are regarded as having to do with the special characteristics of recognizing tones, while front-end processing and feature extraction have been considered essentially independent. Since mismatch between training and testing in signal-space leads to subsequent distortions in feature-space and model-space, determining whether front-end processing and feature extraction is independent or dependent will be critical for robustness.
  • Keywords
    feature extraction; speech recognition; feature extraction; feature space; front-end processing; model space; signal space; subsequent distortions; temporal information; tone recognition; Amplitude modulation; Feature extraction; Hidden Markov models; Speech; Speech recognition; Testing; Training; temporal features; tone recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics - Taiwan (ICCE-TW), 2015 IEEE International Conference on
  • Conference_Location
    Taipei
  • Type

    conf

  • DOI
    10.1109/ICCE-TW.2015.7216924
  • Filename
    7216924