Language identification using spectrogram texture

Abstract

This paper proposes a novel front-end for automatic spoken language recognition, based on the spectrogram representation of the speech signal and in the properties of the Fourier spectrum to detect global periodicity in an image. Local Phase Quantization (LPQ) texture descriptor was used to capture the spectrogram content. Results obtained for 30 seconds test signal duration have shown that this method is very promising for low cost language identification. The best performance is achieved when our proposed method is fused with the i-vector representation.