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A WaveNet Rival? Stanford U Study Models Raw Audio Waveforms Over Contexts of 500k Samples
In the new paper GoodBye WaveNet — A Language Model for Raw Audio with Context of 1/2 Million Samples, Stanford University researcher Prateek Verma presents a generative auto-regressive architecture that models audio waveforms over contexts greater than 500,000 samples and outperforms state-of-the-art WaveNet baselines.
The post A WaveNet Rival? Stanford U Study Models Raw Audio Waveforms Over Contexts of 500k Samples first appeared on Synced.