A straightforward method for automatic identification of marginalized languages

Abstract

Spoken language identification consists in recognizing a language based on a sample of speech from an unknown speaker. The traditional approach for this task mainly considers the phonothactic information of languages. However, for marginalized languages-languages with few speakers or oral languages without a fixed writing standard-, this information is practically not at hand and consequently the usual approach is not applicable. In this paper, we present a method that only considers the acoustic features of the speech signal and does not use any kind of linguistic information. The experimental results on a pairwise discrimination task among nine languages demonstrated that our proposal is comparable to other similar methods. Nevertheless, its great advantage is the straightforward characterization of the acoustic signal. © Springer-Verlag Berlin Heidelberg 2006.