Login / Signup

Dynamic specification of vowels in Hijazi Arabic.

Wael AlmurashiJalal Al-TamimiGhada Khattab
Published in: Phonetica (2024)
Research on various languages shows that dynamic approaches to vowel acoustics - in particular Vowel-Inherent Spectral Change (VISC) - can play a vital role in characterising and classifying monophthongal vowels compared with a static model. This study's aim was to investigate whether dynamic cues also allow for better description and classification of the Hijazi Arabic (HA) vowel system, a phonological system based on both temporal and spectral distinctions. Along with static and dynamic F1 and F2 patterns, we evaluated the extent to which vowel duration, F0, and F3 contribute to increased/decreased discriminability among vowels. Data were collected from 20 native HA speakers (10 females and 10 males) producing eight HA monophthongal vowels in a word list with varied consonantal contexts. Results showed that dynamic cues provide further insights regarding HA vowels that are not normally gleaned from static measures alone. Using discriminant analysis, the dynamic cues (particularly the seven-point model) had relatively higher classification rates, and vowel duration was found to play a significant role as an additional cue. Our results are in line with dynamic approaches and highlight the importance of looking beyond static cues and beyond the first two formants for further insights into the description and classification of vowel systems.
Keyphrases
  • machine learning
  • deep learning
  • magnetic resonance imaging
  • magnetic resonance
  • computed tomography
  • working memory
  • artificial intelligence
  • big data