Rubbing a Physics Based Synthesis Model: From Mouse Control to Frictional Haptic Feedback

This paper investigates three kinds of interactions for a friction based virtual music instrument. The sound synthesis model consists of a bank of mass-spring-dampers excited via rubbing. A nonlinear static friction model capable of reproducing the characteristic stick-slip phenomenon observed in frictional interaction is employed, allowing for dynamic variation of the sliding friction. The different controls developed allow for gradually increasing the interplay between performer and instrument. The key excitation parameters, e.g., the rubbing velocity and the rubbing normal force are controlled using three different interfaces: a standard mouse, a Sensel Morph, and a 3D Systems Touch X. The Sensel Morph is a touchpad with pressure sensitivity, allowing for a natural exertion of the normal force; the 3D Systems Touch X is a haptic device that renders both resistance to the applied normal force, as well as the stick-slip motion resulting from the friction interaction. A preliminary user study aiming to compare the experience of performing with the different interfaces was carried out. The results indicate that the haptic feedback provides a more intuitive and enjoyable experience. However, extra features do not necessarily improve the user interaction, as the results suggest a preference for the mouse over the Sensel

Bowing virtual strings with realistic haptic feedback

We present a music interface implementing a bowed string. The bow is realised using a commercially available haptic device, consisting of a stylus attached to a robotic arm. While playing the virtual strings with the stylus reproducing the bow, users feel both the elastic force from the strings and the friction resulting from the interaction with their surfaces. The audio-haptic feedback is obtained by a physical model: four stiff strings are simulated using a finite difference time domain method, modelled as 1-Delements in the virtual 3-D space. The bow is simply modelled as a rigid cylinder that can move free in this space, and interact with the strings. Finally, the frictional interaction between such elements is modelled by a nonlinear friction model capable of reproducing the characteristic stick-slip phenomenon observed during string bowing. Moreover, the model can be dynamically controlled in one parameter so as to become more sticky or slippery. By turning on and off the frictional feedback, users can appreciate the significance of this interaction. A real-time visualisation of the bowed strings complements the audio-haptic displa

3D ear shape as an estimator of hrtf notch frequency

This paper makes use of a new dataset of Head-Related Transfer Functions (HRTFs) containing high resolution median-plane acoustical measurements of a KEMAR mannequin with 20 different left pinna models as well as 3D scans of the same pinna models. This allows for an investigation of the relationship between 3D ear features and the first pinna notch present in the HRTFs, with the final aim of developing an accurate and handy procedure for predicting the individual HRTF from non-acoustical measurements. We propose a method that takes the 3D pinna mesh and generates a dataset of depth maps of the pinna viewed from various median-plane elevation angles, each having an associated pinna notch frequency value as identified in the HRTF measurements. A multiple linear regression model is then fit to the depth maps, aiming to predict the corresponding first pinna notch. The results of the regression model show moderate improvement to similar previous work built on global and elevation-dependent anthropometric pinna features extracted from 2D images

Perceptual Relevance of Haptic Feedback during Virtual Plucking, Bowing and Rubbing of Physically-Based Musical Resonators

The physics-based design and realization of a digital musical interface asks for the modeling and implementation of the contact-point interaction with the performer. Musical instruments always include a resonator that converts the input energy into sound, meanwhile feeding part of it back to the performer through the same point. Specifically during plucking or bowing interactions, musicians receive a handful of information from the force feedback and vibrations coming from the contact points. This paper focuses on the design and realization of digital music interfaces realizing two physical interactions along with a musically unconventional one, rubbing, rarely encountered in assimilable forms across the centuries on a few instruments. Therefore, it aims to highlight the significance of haptic rendering in improving quality during a musical experience as opposed to interfaces provided with a passive contact point. Current challenges are posed by the specific requirements of the haptic device, as well as the computational effort needed for realizing such interactions without occurrence during the performance of typical digital artifacts such as latency and model instability. Both are however seemingly transitory due to the constant evolution of computer systems for virtual reality and the progressive popularization of haptic interfaces in the sonic interaction design community. In summary, our results speak in favor of adopting nowadays haptic technologies as an essential component for digital musical interfaces affording point-wise contact interactions in the personal performance space

Estimation of Spectral Notches from Pinna Meshes: Insights from a Simple Computational Model

While previous research on spatial sound perception investigated the physical mechanisms producing the most relevant elevation cues, how spectral notches are generated and related to the individual morphology of the human pinna is still a topic of debate. Correctly modeling these important elevation cues, and in particular the lowest frequency notches, is an essential step for individualizing Head-Related Transfer Functions (HRTFs). In this paper we propose a simple computational model able to predict the center frequencies of pinna notches from ear meshes. We apply such a model to a highly controlled HRTF dataset built with the specific purpose of understanding the contribution of the pinna to the HRTF. Results show that the computational model is able to approximate the lowest frequency notch with improved accuracy with respect to other state-of-the-art methods. By contrast, the model fails to predict higher-order pinna notches correctly. The proposed approximation supplements understanding of the morphology involved in generating spectral notches in experimental HRTFs.Design AestheticsIndustrial Design Engineerin