User adaptivity is a key topic in the context of mobile devices and applications, and speech is one the sources of information which has more recently been discovered for this purpose. While considerable work has already been done in both finding algorithms and designing well-performing implementations for this speaker classification task on the desktop platform as part of the AGENDER approach, efforts to bring the results to portable platforms in a working framework have been rather scarce so far. This work seeks to state the major aspects that make mobile speaker classification different from its desktop counterpart, and proposes a number of changes and enhancements to the existing infrastructure to fulfill the requirements emerging from it.
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