Validation of the South Korean Version of the Beliefs about Emotions Scale

Background Beliefs about the unacceptability of experiencing or expressing negative emotions can contribute to diverse psychological symptoms and associated with poor treatment outcomes and low treatment attempts. The Beliefs about Emotions Scale (BES) was developed to assess such beliefs based on the cognitive-behavioral models; however, no study has reported on the psychometric properties of the BES in Korea. The present study aimed to cross-culturally adapt and validate the BES for the Korean population (BES-K). Methods The BES-K was administered to 592 Korean adults (323 men and 269 women) aged 20–59 years. Exploratory and confirmatory factor analysis were used to assess the factor model of the scale. Pearson correlation coefficients were used to evaluate the relationships between the BES-K and other psychological measures. Results The result showed a two-factor model of the BES-K, with Factor 1 relating to Interpersonal and Factor 2 representing Intrapersonal aspects. The scale had significant yet moderately low correlations with measures of depression, anxiety, and difficulties in emotion regulation. Conclusion The BES-K is a useful instrument in evaluating the beliefs about emotions in the Korean population

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

We study contextual linear bandit problems under uncertainty on features; they are noisy with missing entries. To address the challenges from the noise, we analyze Bayesian oracles given observed noisy features. Our Bayesian analysis finds that the optimal hypothesis can be far from the underlying realizability function, depending on noise characteristics, which is highly non-intuitive and does not occur for classical noiseless setups. This implies that classical approaches cannot guarantee a non-trivial regret bound. We thus propose an algorithm aiming at the Bayesian oracle from observed information under this model, achieving $\tilde{O}(d\sqrt{T})$ regret bound with respect to feature dimension $d$ and time horizon $T$. We demonstrate the proposed algorithm using synthetic and real-world datasets.Comment: 30 page

Emotion regulation from a virtue perspective

Background The ability to regulate one’s emotional state is an important predictor of several behaviors such as reframing a challenging situation to reduce anger or anxiety, concealing visible signs of sadness or fear, or focusing on reasons to feel happy or calm. This capacity is referred to as emotion regulation. Deficits in this ability can adversely affect one’s adaptive coping, thus are associated with a variety of other psychopathological symptoms, including but not limited to depression, borderline personality disorder, substance use disorders, eating disorders, and somatoform disorders. Methods The present study examined emotion regulation in relation to the virtue-based psychosocial adaptation model (V-PAM). 595 participants were clustered based on their Difficulties in Emotion Regulation Scale (DERS) score, producing two clusters (i.e., high functioning vs. low functioning). Then, emotion regulation group membership was discriminated by using five V-PAM virtue constructs, including courage, integrity, practical wisdom, committed action, and emotional transcendence. Results Results show that five virtues contribute to differentiating group membership. Practical wisdom was the strongest contributor, followed by integrity, emotional transcendence, committed action, and courage. Predictive discriminant analysis was conducted and 71% of cases were correctly classified. A discussion of the relationship between emotion regulation and virtues was elaborated. Conclusion The concept of virtue holds significant importance in the comprehension of an individual’s capacity to regulate their emotions, meriting future study. Methods: The present study examined emotion regulation in relation to the virtue-based psychosocial adaptation model (V-PAM). 595 participants were clustered based on their Difficulties in Emotion Regulation Scale (DERS) score, producing two clusters (i.e., high functioning vs. low functioning). Then, emotion regulation group membership was discriminated by using five V-PAM virtue constructs, including courage, integrity, practical wisdom, committed action, and emotional transcendence. Results: Results show that five virtues contribute to differentiating group membership. Practical wisdom was the strongest contributor, followed by integrity, emotional transcendence, committed action, and courage. Predictive discriminant analysis was conducted and 71% of cases were correctly classified. A discussion of the relationship between emotion regulation and virtues was elaborated. Conclusion: The concept of virtue holds significant importance in the comprehension of an individual\u27s capacity to regulate their emotions, meriting future study

Validation of the Dimensions of Anger Reactions Scale (the DAR-5) in non-clinical South Korean adults

Background Posttraumatic anger is a commonly reported emotion among people who have experienced traumatic events. The current study aimed to demonstrate the reliability and validity of the South Korean version of the DAR-5 (DAR-5-K). The DAR-5 is a single scale with 5 items which measures posttraumatic anger. The DAR-5 is composed of five items that measure anger frequency, intensity, duration, aggression, and its interference with social relations. Methods Data were collected from 814 South Korean adults who had experienced traumatic events and participated in the study and analyzed via the combination of exploratory factor analysis (n = 405) and confirmatory factor analysis (n = 409). Results Results supported the one-factor structure, as reported in previous validation studies. The scale demonstrated robust internal reliability and concurrent validity with measures of posttraumatic stress disorder (PTSD) symptoms, depression, anxiety, and self-esteem. The DAR-5 cut-off score of 12 that was established in the original validation study successfully differentiated high from low scorers with regard to PTSD symptoms, depression, anxiety, and self-esteem. Conclusion The results confirm that the DAR-5-K is a brief and psychometrically robust measure of anger that can be used to examine South Korean adults who have experienced traumatic events

Visual Speech Recognition for Languages with Limited Labeled Data using Automatic Labels from Whisper

This paper proposes a powerful Visual Speech Recognition (VSR) method for multiple languages, especially for low-resource languages that have a limited number of labeled data. Different from previous methods that tried to improve the VSR performance for the target language by using knowledge learned from other languages, we explore whether we can increase the amount of training data itself for the different languages without human intervention. To this end, we employ a Whisper model which can conduct both language identification and audio-based speech recognition. It serves to filter data of the desired languages and transcribe labels from the unannotated, multilingual audio-visual data pool. By comparing the performances of VSR models trained on automatic labels and the human-annotated labels, we show that we can achieve similar VSR performance to that of human-annotated labels even without utilizing human annotations. Through the automated labeling process, we label large-scale unlabeled multilingual databases, VoxCeleb2 and AVSpeech, producing 1,002 hours of data for four low VSR resource languages, French, Italian, Spanish, and Portuguese. With the automatic labels, we achieve new state-of-the-art performance on mTEDx in four languages, significantly surpassing the previous methods. The automatic labels are available online: https://github.com/JeongHun0716/Visual-Speech-Recognition-for-Low-Resource-LanguagesComment: Accepted at ICASSP 202