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Sorry about the delay. With a GeForce GTX 1080 Ti I'm getting around 3700 samples a second (so almost 0.25x real-time with 16kHz audio) and on an Intel Core i7-8700K CPU @ 3.70GHz I'm getting about 1700 samples a second.
So definitely faster than vanilla WaveNet but not quite real-time. However, since there is only a single forward GRU on the autoregressive path I'm sure you could get better than real-time with some engineering e.g. sparsifying the GRU, designing a custom cuda kernel, etc.
Hi! Could you share some details about the inference speed compared to Griffin-Lim/WaveNet/WaveRNN?
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