Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments
Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an...
| Main Authors: | , , , , , , |
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| Format: | Online |
| Language: | English |
| Published: |
Public Library of Science
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5023122/ |