Papers with Laplacian mixture loss

1 papers
Revisiting Over-Smoothness in Text to Speech (2022.acl-long)

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Challenge: Non-autoregressive text to speech models ignore correlation in time and frequency domains, causing blurry results.
Approach: They revisit the problem of over-smoothness in non-autoregressive text to speech models . they use methods that reduce complexity of data distributions and improve modeling methods .
Outcome: The proposed models achieve better voice quality and faster inference speed than autoregressive models.

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