论文标题
超越格里芬·里姆（Griffin-Lim）：改进了迭代阶段的言语检索
Beyond Griffin-Lim: Improved Iterative Phase Retrieval for Speech
论文作者
论文摘要
阶段检索不仅是语音和音频处理中遇到的问题，而且在许多其他领域（例如光学）中遇到的问题。基于非Convex集投影的迭代算法有效，并且在仅可用的STFT幅度时经常用于检索该相。尽管Griffin-Lim算法及其变体一直是几十年来的普遍方法，但最新进展，例如在光学方面，提出一个问题：使用相同的迭代投影原理，我们可以比格里芬·里姆（Griffin-Lim）做得更好吗？ 在本文中，我们将语音域中的经典算法与光学质量的两种现代方法相比，相对于重建质量和收敛速率进行了比较。基于这项研究，我们建议将Griffin-lim与差异图算法结合在混合方法中，该方法在最终重建的收敛和质量方面显示出了优越的结果。
Phase retrieval is a problem encountered not only in speech and audio processing, but in many other fields such as optics. Iterative algorithms based on non-convex set projections are effective and frequently used for retrieving the phase when only STFT magnitudes are available. While the basic Griffin-Lim algorithm and its variants have been the prevalent method for decades, more recent advances, e.g. in optics, raise the question: Can we do better than Griffin-Lim for speech signals, using the same principle of iterative projection? In this paper we compare the classical algorithms in the speech domain with two modern methods from optics with respect to reconstruction quality and convergence rate. Based on this study, we propose to combine Griffin-Lim with the Difference Map algorithm in a hybrid approach which shows superior results, in terms of both convergence and quality of the final reconstruction.
