> ML_LITERATURE // OORD-2016-WAVENET-GENERATIVE-MODEL-RAW-AUDIO_v1.0
WaveNet: A Generative Model for Raw Audio
Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, Koray Kavukcuoglu · arXiv preprint (2016)
seminal-architecture2016industry-standardthirdPartyReproduced
Principal Contribution
Modeled raw audio waveforms at 16,000 samples per second using autoregressive causal dilated convolutions with exponentially growing receptive fields.
Operational Relevance
Serves as qualified reference for implementing task-text-to-speech in production systems.
Assumptions
- Underlying spatio-temporal continuity and domain distributional stability hold
Limitations
- Performance scaling and computational footprint depend on receptive field depth, sequence length, and resolution