A straightforward method for automatic identification of marginalized languages

  • Authors:

  • Ana Lilia Reyes-Herrera;Luis Villaseñor-Pineda;Manuel Montes-y-Gómez

  • Affiliations:

  • Language Technologies Group, Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Mexico;Language Technologies Group, Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Mexico;Language Technologies Group, Computer Science Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Mexico

  • Venue:
  • FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

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.