基于频率选择外推的语音信号降频
Declipping of Speech Signals Using Frequency Selective Extrapolation
摘要：
在音频信号处理中，对削波后的语音信号进行重构是一项重要的任务，以提高音频质量，便于进一步处理。在本文中，频率选择性外推（FSE），这是通常用于错误隐藏或不完整的图像数据的重建，是适应能够恢复音频信号从削波失真。为此，FSE生成信号的模型作为傅立叶基函数的迭代叠加。然后，可以用来自模型的估计样本替换裁剪样本。使用不同的语音测试数据集对算法的性能进行了评估。与其他最先进的去唇算法相比，这导致SNR的最大增益高达3：5 dB，平均增益为1 dB。
英文摘要：
The reconstruction of clipped speech signals is an important task in audio signal processing to achieve an enhanced audio quality for further processing. In this paper, Frequency Selective Extrapolation (FSE), which is commonly used for error concealment or the reconstruction of incomplete image data, is adapted to be able to restore audio signals which are distorted from clipping. For this, FSE generates a model of the signal as an iterative superposition of Fourier basis functions. Clipped samples can then be replaced by estimated samples from the model. The performance of the proposed algorithm is evaluated by using different speech test data sets. Compared to other state-of-the-art declipping algorithms, this leads to a maximum gain in SNR of up to 3:5 dB and an average gain of 1 dB.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
