  We present two methods of real time magnitude spectrogram inversion:
streaming Griffin Lim(GL) and streaming MelGAN. We demonstrate the impact of
looking ahead on perceptual quality of MelGAN. As little as one hop size
(12.5ms) of lookahead is able to significantly improve perceptual quality in
comparison to its causal version. We compare streaming GL with the streaming
MelGAN and show different trade-offs in terms of perceptual quality, on-device
latency, algorithmic delay, memory footprint and noise sensitivity. For fair
quality assessment of the GL approach, we use input log magnitude spectrogram
without mel transformation. We evaluate presented real time spectrogram
inversion approaches on clean, noisy and atypical speech. We specified
conditions when streaming GL has comparable quality with MelGAN: noisy audio
and no mel transformation. Streaming GL is 2.4x faster than real time on the
ARM CPU of a Pixel4 and it uses 4.5x times less memory than MelGAN.

Audio and Speech Processing;Sound