I recently read Bytenet and Wavenet and I was curious why the first model is not as popular as the second. From my understanding, Bytenet can be seen as a seq2seq model where the encoder and the decoder are similar to Wavenet. Following the trends from NLP where seq2seq models seem to perform better, I find it strange that I couldn't find any paper that compares the two. Are there any drawbacks of Bytenet over Wavenet other than the computation time?
My conclusion is the same as yours that there doesn't seem to be any published comparison of the two models. ByteNet is computationally expensive and requires a lot of parameters. WaveNet improves on ByteNet's efficiency, as you mentioned, and I believe that is the main difference.