Analogy, the Corpus and Pronunciation

  • Kirk P. H. Sullivan
Chapter
Part of the Telecommunications Technology & Applications Series book series (TTAP)

Abstract

Reading aloud and text-to-speech synthesis share the commonality of taking a printed text and generating the acoustic correlate. This chapter starts from the premise that modelling the human solution for generating the pronunciation of a word previously unseen will result in more effective and accurate pronunciation modules for machine synthesis. The human and the text-to-speech system both have access to a lexicon: the mental lexicon in the first case and the system dictionary in the other. These are the data sources which can be mined to generate an unknown word’s pronunciation. This chapter presents a computational approach to automatic pronunciation developed from a psychological model of oral reading. The approach takes the system dictionary — a frequency-tagged corpus — and uses analogy to generate the pronunciation of words not in the dictionary. A range of implementational choices is discussed and the effectiveness of the model for (British) English, German and Māori demonstrated.

Keywords

Confidence Rating Oral Reading Mental Lexicon Input Word Analogy Segment 
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 Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Kirk P. H. Sullivan
    • 1
  1. 1.Department of Philosophy and LinguisticsUmeå UniversitySweden

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