Beta 1


Title Preference based personalization of hearing aids
Author Nielsen, Jens Brehm (Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Supervisor Larsen, Jan (Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2010
Abstract The procedure involved in fitting hearing aids has become highly extensive, due to the vast number of parameters in modern hearing aids. An interactive system that automatically optimizes the hearing aid setting for individual users is an interesting alternative in comparison with manual hearing aid fitting procedures. In this thesis, an iterative interactive framework for personalization of hearing aids based on user preferences is presented. For a particular user, the framework models a preference function over hearing aid settings with a Gaussian process based on a minimum of observations. An observation is a subjective rating of the overall preference of the processed sound resulting from a particular hearing aid setting. New observations are suggested based a novel active learning criterion developed in this project. With the novel active learning criterion the next subjectively rated setting becomes the setting for which the preference has the highest probability of being larger than the preference for the currently preferred setting given a Gaussian process estimated preference function. Simulations and a pilot experiment show that the framework discovers a personalized setting in few iterations compared with the number of possible settings. Furthermore, the framework has the capability to model complex preference functions, although an improved interactive experimental paradigm is required to account for inconsistent subjective preference assessments.
Abstract Den procedure, der kræves for at tilpasse høreapparater, er blevet særdeles omfattende pga. det store antal parametre i moderne høreapparater. Et interaktivt system, som automatisk optimerer høreapparatsindstillinger for individuelle brugere, er et interessant alternativ til manuelle høreapparats tilpasningsprocedurer. I dette speciale præsenteres en interaktiv metode til præference baseret høreapparatspersonliggørelse. For en given bruger modelleres en præferencefunktion over høreapparatsindstillinger med en Gaussisk process baseret på et minimum af observationer. En observation er en subjektiv vurdering af den overordnet præference af den resulterende lyd givet en specifik høreapparatsindstilling. Nye observationer foreslås baseret på et nyt aktivt læringskriterium, som er udviklet i dette projekt. Med det nye aktive læringskriterium bliver den næste subjektive vurderede indstilling, den indstilling for hvilken præferencen har den største sandsynlighed for at være større end præferencen for den nuværende foretrukne indstilling givet en Gaussisk process estimeret præferencefunktion. Simuleringer og et pilot forsøg viser, at metoden finder en personlig indstilling efter få iterationer sammenlignet med antallet af mulige indstillinger. Endvidere har metoden evnen til at modellere komplekse præferencefunktioner, selvom et forbedret interaktivt forsøgsparadigme er nødvendigt for at tage højde for inkonsistente subjektive præference vurderinger.
Imprint Technical University of Denmark (DTU) : Kgs. Lyngby, Denmark
Pages 112
Series IMM-M.Sc.-2010
Fulltext
Original PDF ep10_61_net.pdf (18.35 MB)
Admin Creation date: 2010-08-26    Update date: 2011-11-02    Source: dtu    ID: 266193    Original MXD