Archives of Acoustics, 43, 4, pp. 625–636, 2018
10.24425/aoa.2018.125156

Voice Traces of Anxiety: Acoustic Parameters Affected by Anxiety Disorder

Turgut ÖZSEVEN
Gaziosmanpaşa University
Turkey

Muharrem DÜĞENCI
Karabük University
Turkey

Ali DORUK
Health Science University
Turkey

Hilal İlkay KAHRAMAN
Gülhane Training and Research Hospital
Turkey

Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people’s voice characteristics. In this study, the reflection of anxiety disorder in people’s voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.
Keywords: anxiety; acoustic analysis; signal processing; speech processing
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DOI: 10.24425/aoa.2018.125156

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