Reversible Sound-to-Letter/Letter-to-Sound Modeling Based on Syllable Structure

  title={Reversible Sound-to-Letter/Letter-to-Sound Modeling Based on Syllable Structure},
  author={Stephanie Seneff},
This paper describes a new grapheme-tophoneme framework, based on a combination of formal linguistic and statistical methods. A context-free grammar is used to parse words into their underlying syllable structure, and a set of subword “spellneme” units encoding both phonemic and graphemic information can be automatically derived from the parsed words. A statistical -gram model can then be trained on a large lexicon of words represented in terms of these linguistically motivated subword units… CONTINUE READING
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