The Sabancı University Dynamic Face Database (SUDFace): Development and validation of an audiovisual stimulus set of recited and free speeches with neutral facial expressions.

Şentürk, Yağmur Damla; Tavacioglu, Ebru Ecem; Duymaz, İlker; Sayim, Bilge; Alp, Nihan (2023). The Sabancı University Dynamic Face Database (SUDFace): Development and validation of an audiovisual stimulus set of recited and free speeches with neutral facial expressions. Behavior research methods, 55(6), pp. 3078-3099. Psychonomic Society 10.3758/s13428-022-01951-z

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Faces convey a wide range of information, including one's identity, and emotional and mental states. Face perception is a major research topic in many research fields, such as cognitive science, social psychology, and neuroscience. Frequently, stimuli are selected from a range of available face databases. However, even though faces are highly dynamic, most databases consist of static face stimuli. Here, we introduce the Sabancı University Dynamic Face (SUDFace) database. The SUDFace database consists of 150 high-resolution audiovisual videos acquired in a controlled lab environment and stored with a resolution of 1920 × 1080 pixels at a frame rate of 60 Hz. The multimodal database consists of three videos of each human model in frontal view in three different conditions: vocalizing two scripted texts (conditions 1 and 2) and one Free Speech (condition 3). The main focus of the SUDFace database is to provide a large set of dynamic faces with neutral facial expressions and natural speech articulation. Variables such as face orientation, illumination, and accessories (piercings, earrings, facial hair, etc.) were kept constant across all stimuli. We provide detailed stimulus information, including facial features (pixel-wise calculations of face length, eye width, etc.) and speeches (e.g., duration of speech and repetitions). In two validation experiments, a total number of 227 participants rated each video on several psychological dimensions (e.g., neutralness and naturalness of expressions, valence, and the perceived mental states of the models) using Likert scales. The database is freely accessible for research purposes.

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