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Learning Representations for New Sound Classes With Continual Self-Supervised Learning
Zhepei Wang
, Cem Subakan
, Xilin Jiang
, Junkai Wu
, Efthymios Tzinis
, Mirco Ravanelli
, Paris Smaragdis
Siebel School of Computing and Data Science
Electrical and Computer Engineering
Coordinated Science Lab
Research output
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Dive into the research topics of 'Learning Representations for New Sound Classes With Continual Self-Supervised Learning'. Together they form a unique fingerprint.
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Keyphrases
Continual Learning
66%
Distillation
33%
Encoder
33%
Labeled Data
33%
Learning Context
33%
Learning Framework
33%
Learning Methods
100%
Learning Representations
100%
New Sound
100%
Recognition System
33%
Representation Learning
66%
Self-supervised Learning
100%
Self-supervised Representation Learning
33%
Similarity-based Representation
33%
Sound Recognition
33%
Unlabeled Data
33%
Computer Science
Continual Learning
66%
Learning Framework
33%
Recognition System
33%
Representation Learning
100%
Self-Supervised Learning
100%
Self-Supervised Representation Learning
33%
Unlabeled Data
33%
Use Case
33%