ASSISI Database (Audiovisual Associations Through an Enactive Approach)

Dataset: Audiovisual Associations Through an Enactive Approach

Description

This dataset contains the experimental data from our study "Assessment of the role of emotions in audiovisual associations through an enactive approach" which investigates how music-induced emotions influence the creation of visual imagery.

The experiment was conducted remotely through a web platform between April and June 2022, with 80 participants (34 males and 46 females, mean age 23.07±5.3 years). Participants were divided into two groups to control for familiarity bias: Group A (n=47) completed the entire protocol, while Group B (n=33) completed only part of it.

Dataset Contents

The dataset includes:

Raw responses from the pretest phase assessing visual and musical capabilities

Data from Phase 1 where participants created images while listening to music and rated their emotional responses

Data from Phase 2 where participants viewed images with specific parameter settings and rated their emotional responses

Demographic information and background data from participants

Calculated emotional correspondence indices between music-induced and image-induced emotions

Variables

Key variables include:

Graphical parameters manipulated by participants (Hue, Saturation, Brightness, Shape, Dimension, Dispersion, Numerosity)

Emotional ratings using a 9-point emotional scale (Amazement, Solemnity, Tenderness, Nostalgia, Calmness, Power, Joyful Activation, Tension, Sadness)

Demographic data (age, gender, musical and artistic background)

Results from musical ability tests

Usage Notes

This dataset can be used to study cross-modal associations between auditory and visual stimuli, the role of emotions in mediating these associations, and individual differences in audiovisual perception. The data supports our finding that creating an image while listening to emotionally evocative music results in artwork emotionally coherent with the music.

Citation

If you use this dataset in your research, please cite our paper: Cenerini C, Vollero L, Di Stefano N, Santonico M, Pennazza G, Keller F. Assessment of the role of emotions in audiovisual associations through an enactive approach. Plos One. 2025

Funding

The authors received no specific funding for this work.