  Several recent contributions in the field of iterative STFT phase retrieval
have demonstrated that the performance of the classical Griffin-Lim method can
be considerably improved upon. By using the same projection operators as
Griffin-Lim, but combining them in innovative ways, these approaches achieve
better results in terms of both reconstruction quality and required number of
iterations, while retaining a similar computational complexity per iteration.
However, like Griffin-Lim, these algorithms operate in an offline manner and
thus require an entire spectrogram as input, which is an unrealistic
requirement for many real-world speech communication applications. We propose
to extend RTISI -- an existing online (frame-by-frame) variant of the
Griffin-Lim algorithm -- into a flexible framework that enables straightforward
online implementation of any algorithm based on iterative projections. We
further employ this framework to implement online variants of the fast
Griffin-Lim algorithm, the accelerated Griffin-Lim algorithm, and two
algorithms from the optics domain. Evaluation results on speech signals show
that, similarly to the offline case, these algorithms can achieve a
considerable performance gain compared to RTISI.
