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Detecting Nasal Vowels in Speech Interfaces Based on Surface Electromyography.

João Freitas1, António Teixeira2, Samuel Silva2

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This study shows that electromyography (EMG) sensors can detect velum movement for nasal vowel detection in European Portuguese. This breakthrough enables new speech interface development for languages with nasal sounds.

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Area of Science:

  • Speech processing
  • Biomedical engineering
  • Linguistics

Background:

  • Nasality is crucial in languages like European Portuguese.
  • Detecting nasality via surface electromyography (EMG) presents challenges.
  • Understanding velum movement and muscle activity is key for EMG-based speech interfaces.

Purpose of the Study:

  • To investigate nasality detection using EMG signals.
  • To explore information from velum movement via EMG.
  • To assess deeper facial and neck muscle activity for EMG signal acquisition.

Main Methods:

  • Utilized Real-Time Magnetic Resonance Imaging (RT-MRI) to interpret EMG data.
  • Ensured compatible data recording and time alignment between EMG and RT-MRI.
  • Collected data from multiple speakers for analysis.

Main Results:

  • Identified distinct EMG signal characteristics during nasal vowel utterances.
  • Demonstrated that EMG sensors below the ear can detect velum movement.
  • Achieved nasal vowel detection error rates as low as 32.5% (all speakers) and 23.4% (best speaker).

Conclusions:

  • EMG-based speech interfaces are feasible for languages with nasal characteristics.
  • The proposed method shows promise for developing advanced speech technologies.
  • Further research is encouraged to refine EMG-based speech interface development.