Search arXivSearch

arXiv · 2609.13184

Onomatopoeia Cursor: Verbal Mirroring of Mouse Movement with Comic-Style Lettering

Abstract

The mouse cursor has remained visually mute for half a century: it shows where we point, but says nothing about how we move. We present the Onomatopoeia Cursor, a shipped macOS overlay that classifies cursor kinematics in real time and renders Japanese mimetic words (onomatopoeia) as animated comic-style lettering above the cursor -- "kyorokyoro" (glancing around) for rapid horizontal reversals, "sorosoro" (cautiously) for slow careful motion, "byuun" (whoosh) for fast straight strokes. The system reads seven input channels and displays roughly sixty word forms across five languages. Crucially, the form of each word fluctuates with the manner of action through a morphological generator grounded in Japanese sound symbolism (voicing = weight, gemination = abruptness, elongation = extent, reduplication = iteration). Beyond the rule generator, an on-device onomatopoeia-only transformer (0.4M parameters, 9.7 ms per word) trained on 2,782 mimetic words synthesizes novel forms from the manner of an action; for sound-definite events, a family-anchored generator constrains synthesis to the correct phonetic family. Characters are rendered with hand-drawn outline perturbation, brush-style deformation, and per-character animation grounded in manga lettering conventions. We articulate the design space of verbal motion mirroring, formalize the pipeline as a learnable differentiable mapping, and report a technical evaluation of what is actually implemented and measured. Our central conjecture concerns the sense of agency: formative first-person use suggests that naming a movement while it happens perturbs the felt authorship of the action -- modulation, amplification, and interference -- and we outline a within-subjects study with salience-matched controls as future work. No user-study results are claimed; the contribution is the concept, the working system, and its design space.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Yoichi Ochiai, Miki Okamura. 2026-07-31. Onomatopoeia Cursor: Verbal Mirroring of Mouse Movement with Comic-Style Lettering. https://arxiv.org/abs/2609.13184

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials

Eligibility criteria play a critical role in clinical trials by determining the target patient population, which significantly influences the outcomes of medical interventions. However, current approaches for designing eligibility criteria have limitations to support interactive exploration of the large space of eligibility criteria. They also ignore incorporating detailed characteristics from the original electronic health record (EHR) data for criteria refinement. To address these limitations, we proposed TrialCompass, a visual analytics system integrating a novel workflow, which can empower clinicians to iteratively explore the vast space of eligibility criteria through knowledge-driven and outcome-driven approaches. TrialCompass supports history-tracking to help clinicians trace the evolution of their adjustments and decisions when exploring various forms of data (i.e., eligibility criteria, outcome metrics, and detailed characteristics of original EHR data) through these two approaches. This feature can help clinicians comprehend the impact of eligibility criteria on outcome metrics and patient characteristics, which facilitates systematic refinement of eligibility criteria. Using a real-world dataset, we demonstrated the effectiveness of TrialCompass in providing insights into designing eligibility criteria for septic shock and sepsis-associated acute kidney injury. We also discussed the research prospects of applying visual analytics to clinical trials.

cs.HC

PRIMMDebug: Teaching Secondary School Students a Reflective Approach to Debugging

Debugging is a challenging and infuriating experience for many secondary school students learning their first text-based programming language. One frequent problem is the lack of reflection in students' debugging strategies, which makes error resolution unlikely and teacher reliance common. Tools that encourage more reflective and teacher-independent debugging may foster more success with fixing errors, but are lacking. This paper presents PRIMMDebug, an approach for teaching the debugging process to secondary school students. PRIMMDebug consists of an online tool that takes students through the steps of a pedagogical process based on PRIMM, a framework for teaching programming. The tool encourages written articulation throughout the debugging process and limits students' ability to run and edit code at certain stages. A classroom study with PRIMMDebug found a general reluctance among students to engage with the reflection it promotes, despite teachers appreciating this emphasis on reflection. We end by suggesting three considerations for future pedagogical debugging research and tooling: balance structure and flexibility, teach shorter debugging heuristics, and use tooling early on in students' programming journey.

cs.HC

Mirror Skin: In Situ Visualization of Robot Touch Intent on Robotic Skin

Effective communication of robot touch intent is essential for safe and predictable physical human-robot interaction. While intent communication has been widely studied, existing approaches lack the spatial specificity and semantic depth necessary to efficiently convey robot touch intent. We present Mirror Skin, a cephalopod inspired concept that mirrors in-situ visual representations of a human's body parts onto the corresponding robot's touch region to communicate who shall initiate touch, where it will occur, and when it is imminent. We informed the design of Mirror Skin through a structured design exploration with experts and demonstrate the real-world feasibility of Mirror Skin with a proof-of-concept prototype. User studies in VR and with the physical prototype showed that Mirror Skin significantly improves accuracy and response times for interpreting touch intent and improves the user experience during physical human-robot interactions.

cs.HC