A novel implementation of the spectral shaping approach for artificial bandwidth extension

We present a novel implementation of the spectral shaping approach for artificial bandwidth extension (ABE). The spectral envelope in the missing band is adaptively tuned by a set of controlled subband powers predicted by a feedforward neural network (FFNN) in conjunction with the use of spline interpolation. There are three main aspects to this study: First, objective quality measures are exploited to select a proper feature vector, to choose relevant critical subbands and to train the network effectively. Second, the extensions toward high and low frequencies are evaluated explicitly. Third, a large assortment of empirical results on speech quality and speech intelligibility is provided. The obtained results indicate a significant improvement of the extended speech w.r.t. the narrowband speech.