标题： 用于音频分类模型的时间局部解释的基准测试 显示英文标题

标题： Benchmarking Time-localized Explanations for Audio Classification Models

摘要： 大多数现代音频处理方法是不透明的，也就是说，它们不会为其决策提供解释。 因此，已经提出了各种方法来解释这些模型生成的输出。 好的解释可以带来关于数据或模型的有趣见解，并增加对系统的信任。 不幸的是，评估解释的质量远非简单，因为对于大多数任务来说，没有明确的真值解释可供参考。 在本工作中，我们提出了一种用于音频分类模型的时间定位解释的基准，该基准使用目标事件的时间注释作为真值解释的代理。 我们使用这个基准系统地优化和比较各种模型无关的后期解释方法，在某些情况下，获得了接近完美的解释。 最后，我们展示了解释在揭示虚假相关性方面的实用性。 显示英文摘要

摘要： Most modern approaches for audio processing are opaque, in the sense that they do not provide an explanation for their decisions. For this reason, various methods have been proposed to explain the outputs generated by these models. Good explanations can result in interesting insights about the data or the model, as well as increase trust in the system. Unfortunately, evaluating the quality of explanations is far from trivial since, for most tasks, there is no clear ground truth explanation to use as reference. In this work, we propose a benchmark for time-localized explanations for audio classification models that uses time annotations of target events as a proxy for ground truth explanations. We use this benchmark to systematically optimize and compare various approaches for model-agnostic post-hoc explanation, obtaining, in some cases, close to perfect explanations. Finally, we illustrate the utility of the explanations for uncovering spurious correlations.