EmoSynth: The Emotional Synthetic Audio Dataset

The ability of sound to enhance human wellbeing has been known since ancient civilisations, and methods can be found today across domains of health and within a variety of cultures. 

EmoSynth is a dataset of 144 audio files which have been labelled by 40 listeners for their the perceived emotion, in regards to the dimensions of Valence and Arousal.

Results on the dataset show that Arousal does correlate moderately to fundamental frequency, and that the sine waveform is perceived as significantly different to square and sawtooth waveforms when evaluating perceived Arousal. The general results suggest that isolated synthetic audio can be modelled as a means of evoking affective states of emotion.

When using this version of the data for a publication, please cite the following study: 

@inproceedings{Baird:2018:PEI:3243274.3243277,
author = {Baird, Alice and Parada-Cabaleiro, Emilia and Fraser, Cameron and Hantke, Simone and Schuller, Bj\"{o}rn},
title = {The Perceived Emotion of Isolated Synthetic Audio: The EmoSynth Dataset and Results},
booktitle = {Proceedings of the Audio Mostly 2018 on Sound in Immersion and Emotion},
series = {AM'18},
year = {2018},
isbn = {978-1-4503-6609-0},
location = {Wrexham, United Kingdom},
pages = {7:1--7:8},
articleno = {7},
numpages = {8},
url = {http://doi.acm.org/10.1145/3243274.3243277},
doi = {10.1145/3243274.3243277},
acmid = {3243277},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {affective computing, perception, sound healing, synthetic audio, wellbeing},
}