Phase reconstruction in speech synthesis refers to the process of recreating the phase information of a speech signal. In speech synthesis, the goal is to generate artificial speech that sounds natural and intelligible. Speech synthesis systems based on [[statistical parametric synthesis (SPSS)]] or [[neural speech synthesis]] typically represent the predicted [[acoustic features]] for synthesis in the form of the magnitude of the [[intermediate spectrogram]]. However, phase information is equally important for speech perception and naturalness. The phase carries temporal information and is responsible for the fine details of the speech signal, including the characteristics of different phonemes and the transitions between them. Without accurate phase reconstruction, the synthesized speech may lack clarity and sound unnatural. Phase reconstruction techniques aim to estimate the original phase information based on the available spectral information. Various algorithms and approaches have been developed to tackle this challenge. The [[Griffin-Lim algorithm]] is a pure signal-processing approach to phase reconstruction that iteratively reconstructs phase information from just the magnitude spectrogram,