论文标题
一种迭代图谱频谱减法方法，用于增强语音
An Iterative Graph Spectral Subtraction Method for Speech Enhancement
论文作者
论文摘要
在本文中，我们研究了图形信号处理（GSP）理论在语音增强中的应用。我们首先提出一组移位运算符来构建图形语音信号，然后在图傅立叶域中分析其频谱。通过利用图形语音和图形噪声信号的光谱之间的差异，我们进一步提出了图谱减法（GSS）方法来抑制噪声语音中的噪声干扰。此外，基于GSS，我们提出了迭代图形光谱减法（IGSS）方法，以进一步改善语音增强性能。我们的实验结果表明，所提出的操作员适用于图语音信号，而所提出的方法优于传统的基本光谱减法（BSS）方法和迭代性基本频谱减法（IBSS）方法，就信号 - 噪声比率（SNR）和平均感知评估而言，对语音质量的平均值评估（PESQ）。
In this paper, we investigate the application of graph signal processing (GSP) theory in speech enhancement. We first propose a set of shift operators to construct graph speech signals, and then analyze their spectrum in the graph Fourier domain. By leveraging the differences between the spectrum of graph speech and graph noise signals, we further propose the graph spectral subtraction (GSS) method to suppress the noise interference in noisy speech. Moreover, based on GSS, we propose the iterative graph spectral subtraction (IGSS) method to further improve the speech enhancement performance. Our experimental results show that the proposed operators are suitable for graph speech signals, and the proposed methods outperform the traditional basic spectral subtraction (BSS) method and iterative basic spectral subtraction (IBSS) method in terms of both signal-to-noise ratios (SNR) and mean Perceptual Evaluation of Speech Quality (PESQ).
