Speaker and phoneme-aware speech bandwidth extension with residual dual-path network

Abstract

Speech bandwidth extension aims to generate a wideband signal from a narrowband (low-band) input by predicting the missing high-frequency components. It is believed that the general knowledge about the speaker and phonetic content strengthens the prediction. In this paper, we propose to augment the low-band acoustic features with i-vector and phonetic posteriorgram (PPG), which represent speaker and phonetic content of the speech, respectively. We also propose a residual dual-path network (RDPN) as the core module to process the augmented features, which fully utilizes the utterance-level temporal continuity information and avoids gradient vanishing. Experiments show that the proposed method achieves 20.2% and 7.0% relative improvements over the best baseline in terms of log-spectral distortion (LSD) and signal-to-noise ratio (SNR), respectively. Furthermore, our method is 16 times more compact than the best baseline in terms of the number of parameters.