AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark

Sören Becker, Johanna Vielhaben, Marcel Ackermann, Klaus-Robert Müller, Sebastian Lapuschkin, Wojciech Samek

Abstract: Highlights•We present a novel audio dataset consisting of 30,000 audio samples of spoken digits.•We use LRP to explain predictions of two different models in the audio domain.•We confirm hypotheses about the neural networks’ use of features from explanations.•We present audible explanations and demonstrate their superior interpretability.