Measuring the quality of noisy speech signals has been an increasingly important problem in the field of speech processing as more and more speech-communication and human-machine-interface systems are deployed in practical applications. In this paper, we study four widely used classical performance measures: signal-to-distortion ratio (SDR), short-time objective intelligibility (STOI), signal-to-noise ratio (SNR), and perceptual evaluation of speech quality (PESQ). Through analyzing these performance measures under the same framework and identifying the relationship between their core parameters, we convert these measures into the corresponding equivalent SNRs. This conversion enables not only some new insights into different quality measures but also a way to combine these measures into a new metric. In the derivation of the equivalent SNRs, we introduce the widely used masking technique into the computation of correlation coefficients, which is subsequently used to analyze STOI. Furthermore, we propose an attention method to compute the core parameters of PESQ, and also an empirical formula to project the equivalent SNRs into PESQ scores. Experiments are carried out and the results justifies the properties of the derived quality measures.

中文翻译：

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关于侵入式语音质量测量和基于全局 SNR 的度量

随着越来越多的语音通信和人机界面系统被部署在实际应用中，测量噪声语音信号的质量已成为语音处理领域中日益重要的问题。在本文中，我们研究了四种广泛使用的经典性能指标：信号失真比（SDR）、短时客观清晰度（STOI）、信噪比（SNR）和语音质量感知评估（PESQ） ）。通过在同一框架下分析这些性能指标并确定其核心参数之间的关系，我们将这些指标转换为相应的等效信噪比。这种转换不仅可以对不同的质量衡量标准产生一些新的见解，而且还提供了一种将这些衡量标准组合成新指标的方法。在推导等效信噪比时，我们将广泛使用的掩蔽技术引入到相关系数的计算中，随后用于分析 STOI。此外，我们提出了一种注意方法来计算 PESQ 的核心参数，以及一个将等效 SNR 投影到 PESQ 分数的经验公式。进行了实验，结果证明了所得出的质量测量的特性。