LingoMotion: An Interpretable and Unambiguous Symbolic Representation for Human Motion

2026-03-13

AI Summary

Existing human motion representations often rely on black-box latent vectors or joint positions, lacking interpretability and prone to ambiguity. Inspired by the hierarchical structure of natural language, this work proposes LingoMotion—a symbolic, interpretable, and unambiguous motion representation framework. LingoMotion introduces linguistic hierarchy into motion modeling for the first time, constructing a motion alphabet based on joint angles and systematically composing atomic motions into complex activities through morphological rules and syntactic structures that form motion “words” and “phrases.” Experiments on the large-scale Motion-X dataset demonstrate that LingoMotion faithfully captures motion semantics and their attributes—such as speed and scale—significantly enhancing both interpretability and expressive power of motion representations.

Technology Category

• Computer Vision: Motion & Tracking
• Natural Language Processing: Lexical Semantics and Morphology
• Intelligent Robots: Motion and Path Planning

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Existing representations for human motion, such as MotionGPT, often operate as black-box latent vectors with limited interpretability and build on joint positions which can cause ambiguity. Inspired by the hierarchical structure of natural languages - from letters to words, phrases, and sentences - we propose LingoMotion, a motion language that facilitates interpretable and unambiguous symbolic representation for both simple and complex human motion. In this paper, we introduce the concept design of LingoMotion, including the definitions of motion alphabet based on joint angles, the morphology for forming words and phrases to describe simple actions like walking and their attributes like speed and scale, as well as the syntax for describing more complex human activities with sequences of words and phrases. The preliminary results, including the implementation and evaluation of motion alphabet using a large-scale motion dataset Motion-X, demonstrate the high fidelity of motion representation.

Problem

• human motion representation
• interpretability
• ambiguity
• symbolic representation
• motion modeling

Innovation

• LingoMotion
• symbolic representation
• interpretable motion
• motion alphabet
• hierarchical motion language