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Subsegmental level analysis of high arousal speech using the zero-time windowing method.

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This study identifies high arousal speech using the zero-time windowing (ZTW) method. Distinctive spectral features in the glottal open region help accurately detect emotional speech without needing neutral speech as a reference.

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Area of Science:

  • Speech Science
  • Acoustic Phonetics
  • Signal Processing

Background:

  • High arousal speech, associated with emotions like anger and happiness, exhibits altered production characteristics.
  • Traditional acoustic parameters like glottal closed quotient and fundamental frequency (F0) are used to analyze such speech.

Purpose of the Study:

  • To characterize high arousal speech using features extracted from the zero-time windowing (ZTW) method.
  • To develop an effective method for identifying high arousal speech based on these spectral features.

Main Methods:

  • Utilizing the zero-time windowing (ZTW) method to extract instantaneous spectral characteristics from speech signals.
  • Analyzing spectral changes in the lower frequency range during the glottal open region.
  • Developing identification rules based on distinctive spectral features observed in high arousal speech.

Main Results:

  • The ZTW method highlights changes in the lower frequency spectrum during the glottal open phase.
  • Distinctive spectral features were identified in high arousal speech compared to neutral speech.
  • Simple rule-based identification achieved good performance in detecting high arousal speech.

Conclusions:

  • The ZTW method effectively captures spectral features indicative of high arousal speech.
  • The identified spectral features enable accurate detection of emotional speech.
  • The proposed method shows promise for real-time identification of high arousal speech.