  The paper presents a hierarchical naive Bayesian and lexicon based classifier
for short text language identification (LID) useful for under resourced
languages. The algorithm is evaluated on short pieces of text for the 11
official South African languages some of which are similar languages. The
algorithm is compared to recent approaches using test sets from previous works
on South African languages as well as the Discriminating between Similar
Languages (DSL) shared tasks' datasets. Remaining research opportunities and
pressing concerns in evaluating and comparing LID approaches are also
discussed.
