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Syllabification by phone categorization

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Abstract

Syllables play an important role in speech synthesis, speech recognition, and spoken document retrieval. A novel, low cost, and language agnostic approach to dividing words into their corresponding syllables is presented. A hybrid genetic algorithm constructs a categorization of phones optimized for syllabification. This categorization is used on top of a hidden Markov model sequence classifier to find syllable boundaries. The technique shows promising preliminary results when trained and tested on English words.

Bibliographic Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Original language

English

Pages from-to (Number of pages)

Pages 47-48 (2 pages)

Publication milestones

  • Published - 06/07/2018

Publication status

Published - 06/07/2018

Publisher

Association for Computing Machinery, Inc

Publication series

  • Publication series name: GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

ISBN (Electronic)

9781450357647

Publication IDs

  • Scopus: 85051454046

Host publication title

GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion