{ "access": { "embargo": { "active": false, "reason": null }, "files": "restricted", "record": "public", "status": "restricted" }, "created": "2020-04-24T17:44:33.182424+00:00", "custom_fields": {}, "deletion_status": { "is_deleted": false, "status": "P" }, "files": { "enabled": true }, "id": "3762962", "is_draft": false, "is_published": true, "links": { "access": "https://zenodo.org/api/records/3762962/access", "access_links": "https://zenodo.org/api/records/3762962/access/links", "access_request": "https://zenodo.org/api/records/3762962/access/request", "access_users": "https://zenodo.org/api/records/3762962/access/users", "archive": "https://zenodo.org/api/records/3762962/files-archive", "archive_media": "https://zenodo.org/api/records/3762962/media-files-archive", "communities": "https://zenodo.org/api/records/3762962/communities", "communities-suggestions": "https://zenodo.org/api/records/3762962/communities-suggestions", "doi": "https://doi.org/10.5281/zenodo.3762962", "draft": "https://zenodo.org/api/records/3762962/draft", "files": "https://zenodo.org/api/records/3762962/files", "latest": "https://zenodo.org/api/records/3762962/versions/latest", "latest_html": "https://zenodo.org/records/3762962/latest", "media_files": "https://zenodo.org/api/records/3762962/media-files", "parent": "https://zenodo.org/api/records/3762961", "parent_doi": "https://zenodo.org/doi/10.5281/zenodo.3762961", "parent_html": "https://zenodo.org/records/3762961", "requests": "https://zenodo.org/api/records/3762962/requests", "reserve_doi": "https://zenodo.org/api/records/3762962/draft/pids/doi", "self": "https://zenodo.org/api/records/3762962", "self_doi": "https://zenodo.org/doi/10.5281/zenodo.3762962", "self_html": "https://zenodo.org/records/3762962", "self_iiif_manifest": "https://zenodo.org/api/iiif/record:3762962/manifest", "self_iiif_sequence": "https://zenodo.org/api/iiif/record:3762962/sequence/default", "versions": "https://zenodo.org/api/records/3762962/versions" }, "media_files": { "enabled": false }, "metadata": { "creators": [ { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Cheul Young Park", "identifiers": [ { "identifier": "0000-0003-0414-272X", "scheme": "orcid" } ], "name": "Cheul Young Park", "type": "personal" } }, { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Narae Cha", "name": "Narae Cha", "type": "personal" } }, { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Soowon Kang", "name": "Soowon Kang", "type": "personal" } }, { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Auk Kim", "name": "Auk Kim", "type": "personal" } }, { "affiliations": [ { "name": "Khalifa University" } ], "person_or_org": { "family_name": "Ahsan Habib Khandoker", "name": "Ahsan Habib Khandoker", "type": "personal" } }, { "affiliations": [ { "name": "Khalifa University" } ], "person_or_org": { "family_name": "Leontios Hadjileontiadis", "name": "Leontios Hadjileontiadis", "type": "personal" } }, { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Alice Oh", "name": "Alice Oh", "type": "personal" } }, { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Yong Jeong", "name": "Yong Jeong", "type": "personal" } }, { "affiliations": [ { "name": "Korea Advanced Institute of Science and Technology (KAIST)" } ], "person_or_org": { "family_name": "Uichin Lee", "name": "Uichin Lee", "type": "personal" } } ], "description": "
While recognizing emotions during social interactions has many potential applications with the popularization of low-cost mobile sensors, the heavy regulation of emotional behaviors in the wild compounds its difficulty. Therefore, studying emotions in the context of social interactions requires a novel dataset comprising multiple modalities and perspectives. 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 during 16 approximately 10 minutes 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 multimodal dataset to accommodate the multiperspective assessment of emotions during social interactions.
", "languages": [ { "id": "eng", "title": { "en": "English" } } ], "publication_date": "2020-04-25", "publisher": "Zenodo", "resource_type": { "id": "dataset", "title": { "de": "Datensatz", "en": "Dataset" } }, "subjects": [ { "subject": "Affective Computing" }, { "subject": "Human-Computer Interaction" } ], "title": "K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations", "version": "0.1.0" }, "parent": { "access": { "owned_by": { "user": 124537 }, "settings": { "accept_conditions_text": "A user must fill out the following form to be granted access to the dataset: https://forms.gle/DUAERhHqf51kyt4Y9
\n\nOnce the form is submitted, we will review it and decide whether to grant or deny access.
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