Bandwidth Extension of Telephone Speech Using a Neural Network and a Filter Bank Implementation for Highband Mel Spectrum

Abstract

The limited audio bandwidth used in narrowband telephone systems degrades both the quality and the intelligibility of speech. This paper presents a new method for the bandwidth extension of telephone speech. Frequency components are added to the frequency band 4-8 kHz using only the information in the narrowband speech. A neural network is used to estimate the mel spectrum in the extension band in short time frames based on features calculated from the narrowband speech. A wideband excitation signal is generated by spectral folding from the narrowband linear prediction residual and a filter bank is utilized to divide the excitation into four sub-bands that cover the extension band. These sub-bands are weighted such that the estimated mel spectrum is realized. Bandwidth-extended speech is obtained by summing the weighted sub-bands and the original narrowband signal. Listening tests show that this new method improves speech quality compared with narrowband telephone speech and with a previously published bandwidth extension method.