Papers by Luis Lugo

1 papers
Towards efficient self-supervised representation learning in speech processing (2024.findings-eacl)

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Challenge: Existing models require several GPUs for days to pretrain, generating environmental concerns because of their high energy consumption.
Approach: They propose an efficient self-supervised model that uses a single GPU during 24 to 48 hours of pretraining to address high computational costs.
Outcome: The proposed model represents two orders of magnitude better than existing models.

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