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A Corpus Balancing Method for Language Model Construction

  • Luis Villaseñor-Pineda
  • Manuel Montes-y-Gómez
  • Manuel Alberto Pérez-Coutiño
  • Dominique Vaufreydaz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2588)

Abstract

The language model is an important component of any speech recognition system. In this paper, we present a lexical enrichment methodology of corpora focused on the construction of statistical language models. This methodology considers, on one hand, the identification of the set of poor represented words of a given training corpus, and on the other hand, the enrichment of the given corpus by the repetitive inclusion of selected text fragments containing these words. The first part of the paper describes the formal details about this methodology; the second part presents some experiments and results that validate our method.

Keywords

Language Model Automatic Speech Recognition Critical Word Training Corpus Speech Recognition System 
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 2003

Authors and Affiliations

  • Luis Villaseñor-Pineda
    • 1
  • Manuel Montes-y-Gómez
    • 1
  • Manuel Alberto Pérez-Coutiño
    • 1
  • Dominique Vaufreydaz
    • 2
  1. 1.Instituto Nacional de AstrofísicaÓptica y Electrónica (INAOE)Mexico
  2. 2.Laboratoire CLIPS-IMAGUniversité Joseph FourierFrance

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