arXiv subjects

Ziyue Piao

Publications and source records attributed to Ziyue Piao.

4 recordsLinked to original sources

arXiv2026

Reconciling Kinesthetic Mismatches: A Somatic Alignment Mindset for Musical Body Transformation

Mastering musical performance requires precise multisensory coordination, yet learners encounter a kinesthetic mismatch, which is a discrepancy between the internal perception of an action and the actual physiological state of the body. While multisensory Body Transformation Experiences (BTE) provide tools to bridge this gap, existing designs often focus on external correction rather than internal alignment. To address this, we propose the Somatic Alignment Mindset (SAM), a conceptual lens that integrates Taoist philosophy to shift the focus of HCI design from prescriptive feedback toward holistic embodied unity. By positioning technology as a reflective medium, SAM operationalizes the principles of Adaptation, Assessment, and Awareness to reconcile somatic discrepancies and foster deep, self-aligned musical mastery.

cs.HC↗

arXiv2026

Exploring Breathing-Music Coupling: Using the Breathing Mirror for Somatic Reflection in Piano Performance

While breathing is essential to living and for sound production in some instruments, for pianists, it is often a hidden and automatic process, making it difficult to analyze or refine. A critical gap exists between data and awareness: while sensors record precise physical metrics, they fail to capture the performer's somatic experience. Conversely, the high cognitive load of performance makes it nearly impossible for musicians to recall their internal states with temporal precision. To address this, we present a system, Breathing Mirror, and associated methodology designed to externalize the pianist's internal somatic experience through three analytical lenses: a Baseline View (synchronized signals), a First-Person View (subjective recall), and an Interpersonal View (collaborative reflection). Through a four-week longitudinal study with a skilled amateur pianist (35 years of experience), we evaluated the system's effectiveness by recording respiratory data using textile-integrated strain sensor belts. The results show that the Breathing Mirror reveals some patterns of breathing-music coupling and identifies critical blind spots where objective data diverges from subjective perception. Furthermore, we propose four somatic themes regarding the link between breathing and musical elements, offering a foundation for future large-scale validation across a broader range of pianists. This work provides a new way to study body signals, transforming breathing from an internal biological function into an articulate expressive parameter.

cs.HC↗

arXiv2024

Enhancing DMI Interactions by Integrating Haptic Feedback for Intricate Vibrato Technique

This paper investigates the integration of force feedback in Digital Musical Instruments (DMI), specifically evaluating the reproduction of intricate vibrato techniques using haptic feedback controllers. We introduce our system for vibrato modulation using force feedback, composed of Bend-aid (a web-based sequencer platform using pre-designed haptic feedback models) and TorqueTuner (an open-source 1 Degree-of-Freedom (DoF) rotary haptic device for generating programmable haptic effects). We designed a formal user study to assess the impact of each haptic mode on user experience in a vibrato mimicry task. Twenty musically trained participants rated their user experience for the three haptic modes (Smooth, Detent, and Spring) using four Likert-scale scores: comfort, flexibility, ease of control, and helpfulness for the task. Finally, we asked participants to share their reflections. Our research indicates that while the Spring mode can help with light vibrato, preferences for haptic modes vary based on musical training background. This emphasizes the need for adaptable task interfaces and flexible haptic feedback in DMI design.

cs.HC↗

arXiv2022

Sensing the Breath: A Multimodal Singing Tutoring Interface with Breath Guidance

Breath is a significant component in singing performance, which is still underresearched in most singing-related music interfaces. In this paper, we present a multimodal system that detects the learner's singing pitch and breathing states and provides real-time visual tutoring feedback. Specifically, the breath detector is a wearable belt with pressure sensors and flexible fabric. It monitors real-time body movement of the abdomen, back waist, and twin ribs. A breath visualization algorithm is developed to display real-time breath states, together with the singing pitch contours on an interactive score interface. User studies show that our system can help users not only gain deeper breath during singing but also improve pitch accuracy in vocal training, especially for those with some musical background.

cs.HC↗