Effort inference and prediction by acoustic and movement descriptors in interactions with imaginary objects during Dhrupad vocal improvisation

Wearable Technol. 2022 Jul 5:3:e14. doi: 10.1017/wtc.2022.8. eCollection 2022.

Abstract

In electronic musical instruments (EMIs), the concept of "sound sculpting" was proposed by Mulder, in which imaginary objects are manually sculpted to produce sounds, although promising has had some limitations: driven by pure intuition, only the objects' geometrical properties were mapped to sound, while effort-which is often regarded as a key factor of expressivity in music performance-was neglected. The aim of this paper is to enhance such digital interactions by accounting for the perceptual measure of effort that is conveyed through well-established gesture-sound links in the ecologically valid conditions of non-digital music performances. Thus, it reports on the systematic exploration of effort in Dhrupad vocal improvisation, in which singers are often observed to engage with melodic ideas by manipulating intangible, imaginary objects with their hands. The focus is devising formalized descriptions to infer the amount of effort that such interactions are perceived to require and classify gestures as interactions with elastic versus rigid objects, based on original multimodal data collected in India for the specific study. Results suggest that a good part of variance for both effort levels and gesture classes can be explained through a small set of statistically significant acoustic and movement features extracted from the raw data and lead to rejecting the null hypothesis that effort is unrelated to the musical context. This may have implications on how EMIs could benefit from effort as an intermediate mapping layer and naturally opens discussions on whether physiological data may offer a more intuitive measure of effort in wearable technologies.

Keywords: Control; Performance augmentation; Performance characterisation; Real-time models; Sensors.