Modeling the emergence of bilingual acoustic clusters: a preliminary case study

  • Authors:
  • Mark Laws;Richard Kilgour;Nikola Kasabov

  • Affiliations:
  • Knowledge Engineering & Discovery Research Institute, Auckland University of Technology, AUT Tech Park, 581-585 Great South Rd, Penrose, Auckland, New Zealand;NAVMAN New Zealand Ltd., P.O. Box 68-155, Newton, Auckland, New Zealand;Knowledge Engineering & Discovery Research Institute, Auckland University of Technology, AUT Tech Park, 581-585 Great South Rd, Penrose, Auckland, New Zealand

  • Venue:
  • Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Spoken language analysis, modeling and recognition-statistical and adaptive connectionist approaches
  • Year:
  • 2003

Quantified Score

Hi-index 0.01

Visualization

Abstract

This paper presents some preliminary results of an original study to model the emergence of bilingual acoustic clusters of both New Zealand English and New Zealand Maori speech. This is performed using true on-line learning in a connectionist architecture. The study represents a joint collaborative analysis, which applies the bilingual data as training examples to a connectionist-based evolving clustering method algorithm. The algorithm returns a structure containing acoustic clusters plotted using visualization techniques that could be used as the foundations for future speech classification systems. The following experiments are based on the notion that approximately 75% of the phonological units in New Zealand English and New Zealand Maori occupy similar acoustic space, they sound the same, and therefore they can be used to classify new unknown speech units or words.