Artículos de revistas
Automatic speaker recognition with Multi-resolution Gaussian Mixture models (MR-GMMs)
Registro en:
10.5769/J200901001
Autor
D’Almeida, Frederico Quadros
Nascimento, Francisco Assis de Oliveira
Berger, Pedro de Azevedo
Silva, Lúcio Martins da
Institución
Resumen
Gaussian Mixture Models (GMMs) are the most widely used technique for voice modeling in automatic speaker recognition systems. In this paper, we introduce a variation of the traditional GMM approach that uses models with variable complexity (resolution). Termed Multi-resolution GMMs (MR-GMMs); this new approach yields more than a 50% reduction in the computational costs associated with proper speaker identification, as compared to the traditional GMM approach. We also explore the noise robustness of the new method by investigating MR-GMM performance under noisy audio conditions using a series of practical identification tests.