Artificial bandwidth extension of narrowband speech using Gaussian Mixture Model

Spectrum of speech signals have frequency components from 50 Hz to 7 kHz (Wideband speech). However, due to historical reasons speech is band-pass filtered between 300 Hz-3.4 kHz in PSTN networks and this speech is referred to as narrowband speech. The missing bandwidth in narrow band speech contributes to speech quality and intelligibility. This paper addresses the problem of artificial bandwidth extension of narrowband speech to wideband speech. The proposed method for bandwidth extension is based on statistical recovery using Gaussian Mixture Model (GMM) for spectral envelope parameters and spectral shifting method is used for excitation extension.