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Improving Thai Spelling Recognition with Tone Features

  • Chutima Pisarn
  • Thanaruk Theeramunkong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4139)

Abstract

Spelling recognition has been used for several purposes, such as enhancing speech recognition systems and implementing name retrieval systems. Tone information is an important clue, in addition to phones, for recognizing speeches in tonal languages. In this paper, we present a method to improve accuracy of spelling recognition in Thai, a tonal language, by incorporating tone-related acoustic features to a well-known front-end feature named Perceptual Linear Prediction Coefficients (PLP). The proposed method makes use of three kinds of tone information: fundamental frequency (pitch), pitch delta and pitch acceleration, to enhance the original features. Compared to the baseline result gained from the original feature, our HMMs-based recognition model shows improvement of 1.73%, 2.85% and 3.16% of letter accuracy for close-type, mix-type and open-type language models, respectively.

Keywords

Feature Vector Speech Recognition Language Model Speech Recognition System Pitch Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chutima Pisarn
    • 1
  • Thanaruk Theeramunkong
    • 1
  1. 1.Sirindhorn International Institute of TechnologyBangkadi, MuangThailand

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