SoundGuides: Adapting Continuous Auditory Feedback to Users

Jules Françoise (1) , Olivier Chapuis (2, 3) , Sylvain Hanneton (4) , Frédéric Bevilacqua (1)

1 STMS - Sciences et Technologies de la Musique et du Son
2 ILDA - Interacting with Large Data
3 LRI - Laboratoire de Recherche en Informatique
4 LPP - UMR 8242 - Laboratoire Psychologie de la Perception

We introduce SoundGuides, a user adaptable tool for auditory feedback on movement. The system is based on a interactive machine learning approach, where both gestures and sounds are first conjointly designed and conjointly learned by the system. The system can then automatically adapt the auditory feedback to any new user, taking into account the particular way each user performs a given gesture. SoundGuides is suitable for the design of continuous auditory feedback aimed at guiding users' movements and helping them to perform a specific movement consistently over time. Applications span from movement-based interaction techniques to auditory-guided rehabilitation. We first describe our system and report a study that demonstrates a 'stabilizing effect' of our adaptive auditory feedback method.

Keywords: Sound and Music Computing; 3D Gestures; Auditory feedback; User Interfaces; Sound; Movement

Domains: Human-Computer Interaction [cs.HC]; Sound [cs.SD]

Jules Françoise, Olivier Chapuis, Sylvain Hanneton, Frédéric Bevilacqua. SoundGuides: Adapting Continuous Auditory Feedback to Users. CHI 2016 - Conference Extended Abstracts on Human Factors in Computing Systems, May 2016, San Jose, United States. pp.2829--2836, ⟨10.1145/2851581.2892420⟩. ⟨hal-01317069⟩