BioS-DB: a multimodal database of individuals in a public speaking scenario, including emotional annotation
Description
The BioS-DB (BioSpeech Database), is a database of indivduals speaking infront of others in both German and English. BioS-DB includes 55 indivdual (33 male and 22 female), with a mean age of 28.9 years ( ± 10.5 years). Individuals were predominately German Natives (33) - and either students (30) or staff from the computer science department at the University of Augsburg, Germany. The average speech length was 45 s for German and 42 s for English.
During the speech, individuals were being evaluated for their emotion (valence / arousal) in a time-continuous way. Individuals were also attached to Blood Volume Pulse, and Skin Conductance sensors, while audio was captured from a lapel microphone and additionally a room microphone.
Alice Baird, Shahin Amiriparian, Miriam Berschnider, Maximilian Schmitt, and Björn Schuller (2019), Predicting Biological Signals from Speech: Introducing a Novel Multimodal Dataset and Results, The Multimodal Signal Processing Conference, Kuala Lumpur, Malaysia, Sept 2019. 5 pages.
Version 2.0: This version contains the raw biological signal, and the individual annotations for re-computing the gold-standard.
Alice Baird, Shahin Amiriparian, Manuel Milling, Björn Schuller (2020), Emotion Recognition in Public Speaking Scenarios Utilising an LSTM-RNN Approach With Attention, The Speech Language Technology Conference, held virtually (to appear) Jan. 2021. 5 pages.
Notes
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The record is publicly accessible, but files are restricted to users with access.
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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:
The user who will make use of the BioS-DB may only use the database after the End User License Agreement (EULA) has been signed and returned to the authors. By signing the EULA, the user agrees to the specific terms of use considered by the authors. The EULA must be signed by a person with a permanent position at an academic institute. The user may not use the database for any non-academic purpose. The user may not distribute the database in any way. All research papers, presentations, or documents that report the use of the BioS-DB will cite the following paper:
Alice Baird, Shahin Amiriparian, Miriam Berschnider, Maximilian Schmitt, and Björn Schuller (2019), Predicting Biological Signals from Speech: Introducing a Novel Multimodal Dataset and Results, The Multimodal Signal Processing Conference, Kuala Lumpur, Malaysia, Sept 2019. no pagination.
To get access, please contact Alice Baird at:
alice.baird@informatik.uni-augsburg.de
Alternative:
alice.baird@ieee.org
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