Using a Neural Network Codec Approximation Loss to Improve Source Separation Performance in Limited Capacity Networks
© 2020 IEEE. A growing need for on-device machine learning has led to an increased interest in light-weight neural networks that lower model complexity while retaining performance. While a variety of general-purpose techniques exist in this context, very few approaches exploit domain-specific proper...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021
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| Online Access: | https://hdl.handle.net/1721.1/137109 |