Using representation learning and out-of-domain data for a paralinguistic speech task

@inproceedings{Milde2015UsingRL,
  title={Using representation learning and out-of-domain data for a paralinguistic speech task},
  author={Benjamin Milde and Christian Biemann},
  booktitle={INTERSPEECH},
  year={2015}
}
In this work, we study the paralinguistic speech task of eating condition classification and present our submitted classification system for the INTERSPEECH 2015 Computational Paralinguistics challenge. We build upon a deep learning language identification system, which we repurpose for general audio sequence classification. The main idea is that we train local convolutional neural network classifiers that automatically learn representations on smaller windows of the full sequence’s spectrum… CONTINUE READING

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