The Indonesian Young-Adult Attachment (IYAA) Dataset: A Multimodal Behavioral Young-Adult Attachment Assessment

IYAA is an Indonesian language-based facial expression and speech for attachment style classification dataset. IYAA consists of Indonesian young-adult audio-video data from diverse age groups between 18-29 years old, with 20 male and 67 female subjects. The data was developed during the COVID-19 pandemic in an online setting by using the Zoom video conference application. Each subject participated in a projective-based attachment assessment which consists of two stages: exposure and response of 14 attachment-based stimuli. The data obtained for each subject includes 14 exposure videos, 14 response videos, and 14 speech response audios. However, two subjects' data are incomplete due to technical issues during data collection. The first subject loses an exposure video, and the second one loses data for a stimulus (an exposure video, a response video, and a speech response audio). So, in total, there are 3650 files, including 1216 exposure videos, 1217 response videos, and 1217 speech response audios. Each data has a varying duration; for exposure video, the minimum duration is 30 seconds, while for response video and speech response audio, the minimum duration is 40 seconds. The data is annotated into two kinds of annotation: attachment and emotion. First, each subject is annotated into one label among three classes of attachment style: secure, insecure anxious, insecure avoidance. Second, each stimulus's data (exposure videos, response videos, and speech response audios) are annotated into one or more labels among eight basic emotions: neutral, happy, sad, contempt, anger, disgust, surprise, and fear. Subject's responses on ECR-RS self-report questionnaire are also extracted to support holistic adult attachment assessment regarding non-verbal behaviors and subjective responses. The IYAA dataset supports multidisciplinary research, specifically on attachment, in Psychology (Behavioral, Social, and Developmental Psychology) and Computer Science (Social Signal Processing).