A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Mask Detection and Breath Monitoring from Speech: on Data Augmentation, Feature Representation and Modeling
[article]
2020
arXiv
pre-print
This paper introduces our approaches for the Mask and Breathing Sub-Challenge in the Interspeech COMPARE Challenge 2020. For the mask detection task, we train deep convolutional neural networks with filter-bank energies, gender-aware features, and speaker-aware features. Support Vector Machines follows as the back-end classifiers for binary prediction on the extracted deep embeddings. Several data augmentation schemes are used to increase the quantity of training data and improve our models'
arXiv:2008.05175v2
fatcat:5icoyftgkza6xik4bsk3pj6yra