Much of the work in speech synthesis has been about closing the gap in vocoders, which take a generated spectrogram and output a waveform. There's a clear gap between practical online implementations and computational behemoths like WaveNet. As you implied it's hard to quantitatively judge which result is better, papers usually use surveys to judge.

Here's a recent work that has a good comparison of some vocoders: https://wavenode-example.github.io/

Edit: WaveRNN struck a good balance for me in the past but is not shown in the link. Tons of new work coming out though!