Wenger Mohr, Maimon Amber, Yizhar Or, Snir Adi, Sasson Yonatan, Amedi Amir
Baruch Ivcher Institute for Brain Cognition and Technology, Baruch Ivcher School of Psychology, Reichman University, Herzliya, Israel.
Department of Cognitive and Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
Front Psychol. 2024 Aug 2;15:1353490. doi: 10.3389/fpsyg.2024.1353490. eCollection 2024.
People can use their sense of hearing for discerning thermal properties, though they are for the most part unaware that they can do so. While people unequivocally claim that they cannot perceive the temperature of pouring water through the auditory properties of hearing it being poured, our research further strengthens the understanding that they can. This multimodal ability is implicitly acquired in humans, likely through perceptual learning over the lifetime of exposure to the differences in the physical attributes of pouring water. In this study, we explore people's perception of this intriguing cross modal correspondence, and investigate the psychophysical foundations of this complex ecological mapping by employing machine learning. Our results show that not only can the auditory properties of pouring water be classified by humans in practice, the physical characteristics underlying this phenomenon can also be classified by a pre-trained deep neural network.
人们可以利用他们的听觉来辨别热属性，尽管在很大程度上他们并未意识到自己能够做到这一点。虽然人们明确声称他们无法通过听到倒水的听觉属性来感知倒水的温度，但我们的研究进一步强化了他们能够做到这一点的认识。这种多模态能力是人类隐性获得的，可能是通过一生接触倒水物理属性差异的感知学习而获得的。在本研究中，我们探索了人们对这种有趣的跨模态对应关系的感知，并通过机器学习研究了这种复杂生态映射的心理物理学基础。我们的结果表明，不仅倒水的听觉属性在实践中可以被人类分类，这一现象背后的物理特征也可以被一个预训练的深度神经网络分类。
