In this paper, we introduce Awear, a context-aware hearing system comprising two state-of-the-art hearing aids, an Android smartphone, and a body-worn Streamer to wirelessly connect them. Awear aims to improve the sound quality perceived by individual hearing aid wearers by learning from their stated preferences. Users personalize, or "train," the system by performing several listening evaluations daily. The Awear app features two types of user-initiated listening evaluations, the A/B Test and the Self-Adjustment Screen. After a longitudinal (6-week) study in which hearing impaired participants (n = 16) used Awear, 10 of the participants stated a preference for training their system using the A/B Test, 3 preferred using the Self-Adjustment Screen, and 3 stated No Preference. Of the 10 who chose the A/B Test, 7 named simplicity or intuitiveness as the primary reason for this preference. We also found a strong correlation between user level of functionality and listening evaluation preference, and a supplemental interview (n = 24) verified this correlation. Lastly, we discuss the most important aspects of the user experience: cognitive, functional, and psychological dimensions. © Springer International Publishing Switzerland 2014.
CITATION STYLE
Aldaz, G., Haydell, T., Szafer, D., Steinert, M., & Leifer, L. (2014). User experience in training a personalized hearing system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8519 LNCS, pp. 3–14). Springer Verlag. https://doi.org/10.1007/978-3-319-07635-5_1
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