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The INTERSPEECH 2014 Computational Paralinguistics Challenge provides for the first time a unified test-bed for the automatic recognition of speakers' cognitive and physical load in speech. In this paper, we describe these two Sub-Challenges, their conditions, baseline results and experimental procedures, as well as the COMPARE baseline features generated(More)
The INTERSPEECH 2015 Computational Paralinguistics Challenge addresses three different problems for the first time in research competition under well-defined conditions: the estimation of the degree of nativeness, the neurological state of patients with Parkinson's condition, and the eating conditions of speakers, i. e., whether and which food type they are(More)
In this work, we present an in-depth analysis of the interdependency between the non-native prosody and the native language (L1) of English L2 speakers, as separately investigated in the Degree of Nativeness Task and the Native Language Task of the INTERSPEECH 2015 and 2016 Computational Paralinguistics ChallengE (ComParE). To this end, we propose a(More)
We present a demonstration of the ARIA framework, a modular approach for rapid development of virtual humans for information retrieval that have linguistic, emotional, and social skills and a strong personality. We demonstrate the framework's capabilities in a scenario where `Alice in Wonderland', a popular English literature book, is embodied by(More)
In this contribution, we propose a novel method for Active Learning (AL) - <i>Dynamic Active Learning (DAL)</i> - which targets the reduction of the costly human labelling work necessary for modelling subjective tasks such as emotion recognition in spoken interactions. The method implements an adaptive query strategy that minimises the amount of human(More)
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