What is recorded here?
Combined a linear-prediction spectral envelope with a WaveRNN-derived neural excitation model to reduce speech-synthesis complexity.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Inherits linear predictive coding and WaveRNN; delta is their specific low-complexity integration. Reported operation budgets and quality depend on conditioning/data/hardware. This original is LPCNet, not WaveGlow.
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People and systems
Jean-Marc Valin; Jan Skoglund
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.
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English catalogue narrative
LPCNet: linear prediction with a recurrent neural excitation model
Combined a linear-prediction spectral envelope with a WaveRNN-derived neural excitation model to reduce speech-synthesis complexity.
Scientific scope
Inherits linear predictive coding and WaveRNN; delta is their specific low-complexity integration. Reported operation budgets and quality depend on conditioning/data/hardware. This original is LPCNet, not WaveGlow.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Jean-Marc Valin; Jan Skoglund
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.