SNIPER Training: Single-Shot Sparse Training for Text-to-Speech

doi:doi:10.57702/n0bfbu9z

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SNIPER Training: Single-Shot Sparse Training for Text-to-Speech

Text-to-speech (TTS) models have achieved remarkable naturalness in recent years, yet like most deep neural models, they have more parameters than necessary. Sparse TTS models can improve on dense models via pruning and extra retraining, or converge faster than dense models with some performance loss.

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Perry Lam, Huayun Zhang, Nancy F. Chen, Berrak Sisman, Dorien Herremans (2024). Dataset: SNIPER Training: Single-Shot Sparse Training for Text-to-Speech. https://doi.org/10.57702/n0bfbu9z

DOI retrieved: December 3, 2024

Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Author	Perry Lam
More Authors	Huayun Zhang Nancy F. Chen Berrak Sisman Dorien Herremans
Homepage	https://github.com/iamanigeeit/sniper