Integrated Speaker Classification for Mobile Shopping Applications
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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- 1.Müller, C.: Zweistufige kontextsensitive Sprecherklassifikation am Beispiel von Alter und Geschlecht. PhD thesis, Computer Science Institute, Saarland University, Germany (2005)Google Scholar
- 2.Feld, M.: Erzeugung von Sprecherklassifikationsmodulen für multiple Plattformen. Master’s thesis, Computer Science Institute, Saarland University, Germany (2006)Google Scholar
- 3.Wasinger, R.: Multimodal Interaction with Mobile Devices: Fusing a Broad Spectrum of Modality Combinations. PhD thesis, Saarland University, Department of Computer Science (2006)Google Scholar
- 4.Heckmann, D.: Ubiquitous User Modeling. PhD thesis, Department of Computer Science, Saarland University (2005)Google Scholar
- 5.Garofolo, J.e.A.: DARPA TIMIT CD-ROM: An Acoustic Phonetic Continous Speech Database. National Institute of Standards and Technology, Gaithersburg, MD, USA (1998)Google Scholar