SelfRemaster: Self-Supervised Speech Restoration for Historical Audio Resources
Restoring high-quality speech from degraded historical recordings is crucial for the preservation of cultural and endangered linguistic resources. A key challenge in this task is the scarcity of paired training data that replicate the original acoustic conditions of the historical audio. While previ...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10366219/ |