Towards a Perceptual Loss: Using a Neural Network Codec Approximation as a Loss for Generative Audio Models
© 2019 Association for Computing Machinery. Generative audio models based on neural networks have led to considerable improvements across fields including speech enhancement, source separation, and text-to-speech synthesis. These systems are typically trained in a supervised fashion using simple ele...
Main Authors: | Ananthabhotla, Ishwarya (Author), Ewert, Sebastian (Author), Paradiso, Joseph A (Author) |
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Other Authors: | Massachusetts Institute of Technology. Media Laboratory (Contributor), Program in Media Arts and Sciences (Massachusetts Institute of Technology) (Contributor) |
Format: | Article |
Language: | English |
Published: |
Association for Computing Machinery (ACM),
2021-12-15T14:32:25Z.
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Subjects: | |
Online Access: | Get fulltext |
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