• Anxiety and mood
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• v.7 no.2
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• pp.85-91
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• 2011

Objective : This study aimed to investigate the characteristics of the early maladaptive schemas in patients with panic disorder. Methods : Patients (n=35) included people who had met the DSM-IV-TR criteria for panic disorder. The normal control group (n=35) were those people who had no psychiatric disorder and had never experienced panic attack. The early maladaptive schemas and the severity of depression and anxiety were assessed by the Young Schema Questionnaire Short-form (YSQ-SF), the Beck Depression Inventory (BDI), and the Spielberger State-Trait Anxiety Inventory (STAI). Results : The scores on the STAI-S, STAI-T, and BDI were significantly higher in the patient group. Compared to the control group, the scores of vulnerability to harm and illness, and abandonment/instability schemas were significantly higher in the patient group. In the patient group, defectiveness/shame and subjugation schemas were found to predict BDI, dependent/incompetence, abandonment/instability schemas were found to predict STAI-S, and vulnerability to harm and illness, and abandonment/instability schemas were found to predict STAI-T. In normal controls, failure and insufficient self-control/self-discipline, failure, and emotion inhibition schemas were found to predict BDI, STAI-T, and STAI-S. Conclusions : Vulnerability to harm and illness and abandonment/instability schemas may be characteristic schema in patients with panic disorder.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.523-529
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• 2021

In this paper, we designed and developed an Emotional Speech Synthesis Markup Language (SSML) processor. Multi-speaker emotional speech synthesis technology that can express multiple voice colors and emotional expressions have been developed, and we designed Emotional SSML by extending SSML for multiple voice colors and emotional expressions. The Emotional SSML processor has a graphic user interface and consists of following four components. First, a multi-speaker emotional text editor that can easily mark specific voice colors and emotions on desired positions. Second, an Emotional SSML document generator that creates an Emotional SSML document automatically from the result of the multi-speaker emotional text editor. Third, an Emotional SSML parser that parses the Emotional SSML document. Last, a sequencer to control a multi-speaker and emotional Text-to-Speech (TTS) engine based on the result of the Emotional SSML parser. Based on SSML which is a programming language and platform independent open standard, the Emotional SSML processor can easily integrate with various speech synthesis engines and facilitates the development of multi-speaker emotional text-to-speech applications.