论文标题
使用频率选择性外推的语音信号拒绝
Declipping of Speech Signals Using Frequency Selective Extrapolation
论文作者
论文摘要
在音频信号处理中重建剪辑的语音信号是实现进一步处理的增强音频质量的重要任务。在本文中，通常用于误差隐藏或重建不完整图像数据的频率选择性外推（FSE），可改用能够恢复从剪辑中扭曲的音频信号。为此，FSE将信号模型作为傅立叶基函数的迭代叠加。然后可以用模型的估计样品代替剪切的样品。通过使用不同的语音测试数据集评估所提出的算法的性能。与其他最先进的算法相比，这会导致SNR的最大增益高达3：5 dB，平均增益为1 dB。
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.
