Abstract
This paper presents an approach to how speaker classification can be used to enable new ways for recommender systems in a mobile shopping environment to bootstrap user models and avoid common problems such as the “early rater”. In a concrete shopping scenario, we introduce the speech-controlled Mobile ShopAssist demonstrator that allows a new customer to more quickly find a product that fulfills his or her demographic group’s specific requirements by exploiting features extracted from speech using the Agender speaker classification system. We propose a method for computing preference scores based on the user’s profile and demonstrate how the application’s GUI can be adapted to deliver the recommendations to the user.
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© 2008 Springer-Verlag Berlin Heidelberg
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Feld, M., Kahl, G. (2008). Integrated Speaker Classification for Mobile Shopping Applications. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds) Adaptive Hypermedia and Adaptive Web-Based Systems. AH 2008. Lecture Notes in Computer Science, vol 5149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70987-9_36
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DOI: https://doi.org/10.1007/978-3-540-70987-9_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70984-8
Online ISBN: 978-3-540-70987-9
eBook Packages: Computer ScienceComputer Science (R0)