AWhat changed
Used a feed-forward transformer and predicted phoneme durations/length regulation to generate mel spectrograms in parallel, learning alignment from an autoregressive teacher.
Scientific scope
Used a feed-forward transformer and predicted phoneme durations/length regulation to generate mel spectrograms in parallel, learning alignment from an autoregressive teacher. Inherits transformers and teacher-student learning. Original teacher alignment/distillation and downstream vocoder costs remain; speedup for acoustic prediction is not necessarily equal full-system speedup or a no-skipping theorem.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits transformers and teacher-student learning. Original teacher alignment/distillation and downstream vocoder costs remain; speedup for acoustic prediction is not necessarily equal full-system speedup or a no-skipping theorem.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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