The INTERSPEECH 2009 emotion challenge
The challenge, the corpus, the features, and benchmark results of two popular approaches towards emotion recognition from speech, and the FAU Aibo Emotion Corpus are introduced.
The INTERSPEECH 2010 paralinguistic challenge
The INTERSPEECH 2010 Paralinguistic Challenge shall help overcome the usually low compatibility of results, by addressing three selected sub-challenges, by address-ing three selected tasks.
The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism
The INTERSPEECH 2013 Computational Paralinguistics Challenge provides for the first time a unified test-bed for Social Signals such as laughter in speech. It further introduces conflict in group…
Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge
The INTERSPEECH 2012 Speaker Trait Challenge
The EPFL-CONF-174360 data indicate that speaker Traits and Likability are influenced by the environment and the speaker’s personality in terms of paralinguistics and personality.
How to find trouble in communication
The HUMAINE Database: Addressing the Collection and Annotation of Naturalistic and Induced Emotional Data
- E. Douglas-Cowie, R. Cowie, K. Karpouzis
- PsychologyAffective Computing and Intelligent Interaction
- 12 September 2007
The HUMAINE Database provides naturalistic clips which record that kind of material, in multiple modalities, and labelling techniques that are suited to describing it.
The INTERSPEECH 2020 Computational Paralinguistics Challenge: Elderly Emotion, Breathing & Masks
The Sub-Challenges, baseline feature extraction, and classifiers based on the ‘usual’ COMPARE and BoAW features as well as deep unsupervised representation learning using the AUDEEP toolkit, and deep feature extraction from pre-trained CNNs using the DEEP SPECTRUM toolkit are described.
The INTERSPEECH 2011 Speaker State Challenge
The INTERSPEECH 2011 Speaker State Challenge addresses two new sub-challenges to overcome the usually low compatibility of results: in the Intoxication Sub-Challenge, alcoholisation of speakers has to be determined in two classes; in the Sleepy Language Corpus, another two-class classification task has to been solved.