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Formant-based vowel categorization for cross-lingual phone recognition.

Marija Stepanović1, Christian Hardmeier1, Odette Scharenborg2

  • 1Department of Computer Science, IT University of Copenhagen, 2300 Copenhagen, Denmark.

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This study improves multilingual phone recognition by using formant frequencies to categorize vowels, enhancing cross-lingual speech technology for underresourced languages. The new method boosts recognition of shared vowels but requires careful implementation for unseen languages.

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Area of Science:

  • Speech Technology
  • Phonetics and Phonology
  • Computational Linguistics

Background:

  • Multilingual phone recognition models leverage language-independent pronunciation patterns for cross-lingual speech applications.
  • Current models often rely on phonological representations, which may not accurately reflect phonetic speech realization, leading to performance degradation.
  • Improving speech technologies for underresourced languages necessitates robust cross-lingual recognition capabilities.

Purpose of the Study:

  • To introduce formant-based vowel categorization for enhanced cross-lingual vowel recognition.
  • To reorganize vowel categories in a multilingual speech corpus for greater cross-lingual consistency.
  • To investigate the impact of formant-based categorization on phone recognition across Danish, Norwegian, and Swedish.

Main Methods:

  • Utilized formant frequencies to determine the phonetic quality of vowels.
  • Applied three categorization techniques to a trilingual, multi-dialect speech corpus (Danish, Norwegian, Swedish).
  • Conducted cross-lingual phone recognition experiments to evaluate the proposed categorization method.

Main Results:

  • Uniting vowel categories into shared formant-based sets improved cross-lingual recognition of common vowels.
  • This approach interfered with the recognition of vowels not present in all training languages.
  • Cross-lingual evaluation on regional dialects yielded inconclusive results, indicating the need for further research.

Conclusions:

  • Formant-based vowel categorization offers a promising avenue for improving cross-lingual speech recognition, particularly for shared vowel sounds.
  • While beneficial for shared vowels, the method's effectiveness for language-specific vowels requires further investigation.
  • Improvements in individual vowel recognition hold potential for enhancing overall phone recognition in unseen languages.