你听到的就是你看到的：从图像质量度量到音频质量度量
What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics
AI总结：
本研究提出利用图像感知度量通过频谱图评估音频质量，基于听觉与视觉神经机制相似性，并定制心理声学度量，在音乐数据集上验证了其与人类感知质量的相关性。
摘要：
在本研究中，我们探讨了利用最先进的图像感知度量通过将音频信号表示为频谱图来评估音频信号的可行性。所提出方法的令人鼓舞的结果基于听觉和视觉通路中神经机制的相似性。此外，我们定制了其中一种具有心理声学合理架构的度量，以适应声音信号的特性。我们使用音乐数据集评估了我们提出的度量及几种基线度量的有效性，在度量与人类评估者评定的音频感知质量之间的相关性方面取得了有希望的结果。
英文摘要：
In this study, we investigate the feasibility of utilizing state-of-the-art image perceptual metrics for evaluating audio signals by representing them as spectrograms. The encouraging outcome of the proposed approach is based on the similarity between the neural mechanisms in the auditory and visual pathways. Furthermore, we customise one of the metrics which has a psychoacoustically plausible architecture to account for the peculiarities of sound signals. We evaluate the effectiveness of our proposed metric and several baseline metrics using a music dataset, with promising results in terms of the correlation between the metrics and the perceived quality of audio as rated by human evaluators.
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。
