Info: Zenodo’s user support line is staffed on regular business days between Dec 23 and Jan 5. Response times may be slightly longer than normal.

There is a newer version of the record available.

Published May 11, 2020 | Version 0.2.0
Dataset Restricted

K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations

  • 1. Korea Advanced Institute of Science and Technology (KAIST)
  • 2. Khalifa University

Description

Recognizing emotions during social interactions has many potential applications with the popularization of low-cost mobile sensors, but a challenge remains with the lack of naturalistic affective interaction data. Most existing emotion datasets are limited for studying idiosyncratic emotions arising in the wild as they were collected in constrained environments. Therefore, studying emotions in the context of social interactions requires a novel dataset, and K-EmoCon is such a multimodal dataset with comprehensive annotations of continuous emotions during naturalistic conversations. The dataset contains multimodal measurements, including audiovisual recordings, EEG, and peripheral physiological signals, acquired with off-the-shelf devices from 16 sessions of approximately 10-minute long paired debates on a social issue. Distinct from previous datasets, it includes emotion annotations from all three available perspectives: self, debate partner, and external observers. Raters annotated emotional displays with 5 seconds intervals while viewing the debate footage, in terms of arousal-valence and 18 additional categorical emotions. The resulting K-EmoCon is the first publicly available emotion dataset accommodating the multiperspective assessment of emotions during social interactions.

Files

Restricted

The record is publicly accessible, but files are restricted to users with access.

Request access

If you would like to request access to these files, please fill out the form below.

You need to satisfy these conditions in order for this request to be accepted:

A user must fill out the following form to be granted access to the dataset: https://forms.gle/DUAERhHqf51kyt4Y9

Once the form is submitted, we will review it and decide whether to grant or deny access.

You are currently not logged in. Do you have an account? Log in here

Additional details

Related works

Is cited by
Preprint: arXiv:2005.04120 (arXiv)