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Abstract:
The INTERSPEECH 2017 Computational Paralinguistics Challenge
addresses three different problems for the first time in research
competition under well-defined conditions: In the Addressee
sub-challenge, it has to be determined whether speech
produced by an adult is directed towards another adult or towards
a child; in the Cold sub-challenge, speech under cold has
to be told apart from ‘healthy’ speech; and in the Snoring subchallenge,
four different types of snoring have to be classified.
In this paper, we describe these sub-challenges, their conditions,
and the baseline feature extraction and classifiers, which include
data-learnt feature representations by end-to-end learning with
convolutional and recurrent neural networks, and bag-of-audiowords
for the first time in the challenge series
