论文标题
评估生成音频系统及其指标
Evaluating generative audio systems and their metrics
论文作者
论文摘要
近年来，通过深层生成模型，音频合成的进展很大。但是，最新的很难量化。在报告结果时，不同的研究通常使用不同的评估方法和不同的指标，从而直接与其他系统进行比较，即使不是不可能。此外，在大多数情况下，所报告的指标的感知相关性和含义都未知，禁止对实际的可用性和音频质量有任何结论性见解。本文介绍了一项研究，该研究与（i）一组先前提出的用于音频重建的客观指标以及（ii）一项听力研究，研究了最先进的方法。结果表明，当前使用的客观指标不足以描述当前系统的感知质量。
Recent years have seen considerable advances in audio synthesis with deep generative models. However, the state-of-the-art is very difficult to quantify; different studies often use different evaluation methodologies and different metrics when reporting results, making a direct comparison to other systems difficult if not impossible. Furthermore, the perceptual relevance and meaning of the reported metrics in most cases unknown, prohibiting any conclusive insights with respect to practical usability and audio quality. This paper presents a study that investigates state-of-the-art approaches side-by-side with (i) a set of previously proposed objective metrics for audio reconstruction, and with (ii) a listening study. The results indicate that currently used objective metrics are insufficient to describe the perceptual quality of current systems.
