There's latency and there's the somewhat separate question of how much time is needed to make a prediction. Wavenet is causal (no look-ahead) and operates on th

There's latency and there's the somewhat separate question of how much time is needed to make a prediction. Wavenet is causal (no look-ahead) and operates on the sample level so there are no buffers and thus no latency in the strict sense, beyond encoding/decoding into the sample rate and format required by the ML model, which should take <1ms. Whether a model manages to make a prediction in that amount of time depends on things like the receptive field and number of layers. The linked paper says their custom implementation runs at 1.1x real-time. I guess this isn't impossible; their receptive field is ~40ms, vs. 300 for the original (notoriously slow) wavenet, and the model is likely to have less layers and channels.