We present a novel way of accounting for similarity judgments. Our approach posits that similarity stems from three main sources-familiarity, priming, and inherent perceptual likeness. Here, we explore each of these constructs and demonstrate their individual and combined effectiveness in explaining similarity judgments. Using these three measures, our account of similarity explains ratings of ...

We present a novel way of accounting for similarity judgments. Our approach posits that similarity ratings stem from three main sources: familiarity, priming, and inherent perceptual similarity. We present a process model of our approach in the cognitive architecture ACT-R, and match our model’s predictions to data collected from a human subject experiment which involved simple perceptual stimu...

Measuring the similarity of images is a fundamental problem to computer vision for which no universal solution exists. While simple metrics such as pixel-wise L2-norm have been shown significant flaws, they remain popular. One group recent state-of-the-art that mitigates some those flaws are Deep Perceptual Similarity (DPS) metrics, where evaluated distance in deep features neural networks.Howe...

Abstract Our study proposes the use of a free classification task for investigating dimensions used by listeners in their perception nonnative sounds and predicting perceptual discriminability contrasts. In task, participants freely group auditory stimuli based on perceived similarity. The results can be to predict compared various acoustic or phonological determine relevant cues listeners. via...