  This work explores the application of various supervised classification
approaches using prosodic information for the identification of spoken North
S\'ami language varieties. Dialects are language varieties that enclose
characteristics specific for a given region or community. These characteristics
reflect segmental and suprasegmental (prosodic) differences but also high-level
properties such as lexical and morphosyntactic. One aspect that is of
particular interest and that has not been studied extensively is how the
differences in prosody may underpin the potential differences among different
dialects. To address this, this work focuses on investigating the standard
acoustic prosodic features of energy, fundamental frequency, spectral tilt,
duration, and their combinations, using sequential and context-independent
supervised classification methods, and evaluated separately over two different
units in speech: words and syllables. The primary aim of this work is to gain a
better understanding on the role of prosody in identifying among the different
language varieties. Our results show that prosodic information holds an
important role in distinguishing between the five areal varieties of North
S\'ami where the inclusion of contextual information for all acoustic prosodic
features is critical for the identification of dialects for words and
syllables.
