University of Oulu

Schuller, B., Steidl, S., Batliner, A., Marschik, P. B., Baumeister, H., Dong, F., Hantke, S., Pokorny, F. B., Rathner, E.-M., Bartl-Pokorny, K. D., Einspieler, C., Zhang, D., Baird, A., Amiriparian, S., Qian, K., Ren, Z., Schmitt, M., Tzirakis, P., & Zafeiriou, S. (2018, September 2). The INTERSPEECH 2018 Computational Paralinguistics Challenge: Atypical and Self-Assessed Affect, Crying and Heart Beats. Interspeech 2018. Interspeech 2018.

The INTERSPEECH 2018 computational paralinguistics challenge : atypical & self-assessed affect, crying & heart beats

Saved in:
Author: Schuller, Björn W.1,2,3; Steidl, Stefan4; Batliner, Anton2,4;
Organizations: 1GLAM – Group on Language, Audio & Music, Imperial College London, UK
2ZD.B Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany
3audEERING GmbH, Gilching, Germany
4Pattern Recognition Lab, FAU Erlangen-Nuremberg, Germany
5iDN – interdisciplinary Developmental Neuroscience, Medical University of Graz, Austria
6University Medical Center Göttingen, Germany
7Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
8Department of Clinical Psychology and Psychotherapy, University of Ulm, Germany
9Shenzhen University General Hospital, Shenzhen, P.R. China
10Machine Intelligence & Signal Processing Group, Technische Universität München, Germany
11University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
Persistent link:
Language: English
Published: International Speech Communication Association, 2018
Publish Date: 2020-03-03


The INTERSPEECH 2018 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the Atypical Affect Sub-Challenge, four basic emotions annotated in the speech of handicapped subjects have to be classified; in the Self-Assessed Affect Sub-Challenge, valence scores given by the speakers themselves are used for a three-class classification problem; in the Crying Sub-Challenge, three types of infant vocalisations have to be told apart; and in the Heart Beats Sub-Challenge, three different types of heart beats have to be determined. We describe the Sub-Challenges, their conditions and baseline feature extraction and classifiers, which include data-learnt (supervised) feature representations by end-to-end learning, the ‘usual’ ComParE and BoAW features and deep unsupervised representation learning using the AUDEEP toolkit for the first time in the challenge series.

see all

Series: Interspeech
ISSN: 1990-9772
ISSN-L: 1990-9772
ISBN Print: 978-1-5108-7221-9
Pages: 122 - 126
DOI: 10.21437/Interspeech.2018-51
Host publication: 19th Annual Conference of the International Speech Communication, INTERSPEECH 2018
Host publication editor: Sekhar, C.C.
Rao, P.
Ghosh, P.K.
Murthy, H.A.
Yegnanarayana, B.
Umesh, S.
Alku, P.
Prasanna, S.R.M.
Narayanan, S.
Conference: Annual Conference of the International Speech Communication
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Copyright information: © The Authors 2018.