Text Input Using Speaker-Adaptive Connected Syllable Recognition

Authors

  • Yoichi Takebayashi
  • Hiroyuki Tsuboi
  • Shouichi Hirai
  • Hiroshi Matsura
  • Tsuneo Nitta

Abstract

This paper describes a speech recognition system for large vocabulary text input. The system recognizes connected Japanese syllables by both continuous pattern matching and speaker-adaptation based on the Multiple Similarity (MS) method. The recognition algorithm consists of syllabic boundary detection, vowel and consonant recognition and lexical verification. The reference pattern vectors adapt to each speaker by K-L expansion through covariance matrix modification. Recognition experiments on a 17,877 word Japanese vocabulary showed 92.6% accuracy for 10 male 4,400 phrase utterances.

Additional Files

Published

2022-12-03

How to Cite

1.
Takebayashi Y, Tsuboi H, Hirai S, Matsura H, Nitta T. Text Input Using Speaker-Adaptive Connected Syllable Recognition. Canadian Acoustics [Internet]. 2022 Dec. 3 [cited 2024 Apr. 15];14(3 bis):105-6. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/3548

Issue

Vol. 14 No. 3 bis (1986): Montreal Symposium On Speech Recognition

Section

Proceedings of the Acoustics Week in Canada

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