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Abstract We propose a two-step approach for reconstructing a signal $$\textbf x\in \mathbb{C}^d$$ from subsampled discrete short-time Fourier transform magnitude (spectogram) measurements: first, we use an aliased Wigner distribution deconvolution approach to solve for a portion of the rank-one matrix $$\widehat{\textbf{x}}\widehat{\textbf{x}}^{*}.$$ Secondly, we use angular synchronization to solve for $$\widehat{\textbf{x}}$$ (and then for $$\textbf{x}$$ by Fourier inversion). Using this method, we produce two new efficient phase retrieval algorithms that perform well numerically in comparison to standard approaches and also prove two theorems; one which guarantees the recovery of discrete, bandlimited signals $$\textbf{x}\in \mathbb{C}^{d}$$ from fewer than $$d$$ short-time Fourier transform magnitude measurements and another which establishes a new class of deterministic coded diffraction pattern measurements which are guaranteed to allow efficient and noise robust recovery.