On the complementarity of short-time fourier analysis windows of different lengths for improved language recognition
Mireia Díez, Mikel Peñagarikano, Germán Bordel, Amparo Varona, Luis Javier Rodríguez-Fuentes · 2014
Previous works have shown that remarkable perfor-mance improvements can be attained in speaker and lan-guage recognition tasks by combining several heteroge-neous systems that provide complementary information. In this work, the complementarity of several i-vector lan-guage recognition systems, using Mel-Frequency Cep-stral-Coefficient (MFCC) features computed on Short-Time Fourier Analysis windows of different sizes, is stud-ied. Language recognition experiments carried out on the NIST 2007 and 2009 LRE datasets reveal relative per-formance gains of up to 33 % when fusing the systems, with regard to the best single system. Results suggest that combining acoustic systems based on analysis win-dows of different sizes may allow to get advantage from both the sharper characterization of short events provided by short windows and the better frequency resolution of stationary events provided by long windows.