Chinese sensorimotor and embodiment norms for 3,000 lexicalized concepts

TL;DR

This paper introduces a comprehensive Mandarin Chinese sensorimotor norm database for 3,000 concepts, validating its reliability and exploring how sensorimotor and embodied knowledge influence lexical processing and can be inferred from linguistic data.

Contribution

It provides the first large-scale, multi-dimensional sensorimotor norm resource for Mandarin Chinese concepts, with validation and analysis of embodied knowledge in language processing.

Findings

High reliability and validity of the normative ratings.

Sensorimotor ratings predict lexical decision performance.

Sensorimotor information can be partially recovered from linguistic representations.

Abstract

Understanding how conceptual knowledge is grounded in bodily experience, and to what extent machine systems can acquire such knowledge without direct sensorimotor experience, are central questions in both cognitive science and embodied artificial intelligence research. Large-scale normative resources are essential for investigating these questions empirically, yet such resources remain sparse for non-Indo-European languages. We present a novel normative database for 3,000 lexicalized concepts in Mandarin Chinese, comprising 11-dimensional sensorimotor ratings and unidimensional embodiment ratings collected from 378 native Mandarin speakers. The ratings demonstrate high reliability and strong cross-norm validity with existing Chinese resources, each of which covers fewer words and a subset of the 11 sensorimotor dimensions. In a validation study, we tested new variables derived from a theoretically motivated metric, Perceptual Strength of Embodiment (PSE) (Huang et al., 2025), together with seven common composite variables, on lexical decision tasks. The results suggest that PSE-Sensorimotor and Minkowski-3 are the strongest composite predictors of lexical decision performance, capturing the facilitatory effects of sensorimotor information on lexical processing. A further exploratory study showed that sensorimotor ratings are substantially recoverable from purely linguistic representations using simple regression models (mean Spearman r = .62 across dimensions), though recovery varied markedly: visual and auditory dimensions yielded higher correspondence than chemosensory ones. Representational similarity analysis further showed that the relational geometry of the sensorimotor space is also partially recoverable (r = .540), consistent with the view that distributional language use encodes aspects of embodied conceptual structure.