Individual Sub-Band Estimation Approach to Bandwidth Extension and Enhancement of Coded Speech

Abstract

The streaming Sound EnhAncement Network (SEANet) has demonstrated impressive performance for speech bandwidth extension (BWE) with low latency and computational complexity. Although the streaming SEANet was designed for voice communication systems, it was not tested with decoded signals that included coding artifacts. Our preliminary experiment showed that the output of the streaming SEANet for the decoded speech had room for improvement even if it was trained with decoded speeches, possibly because it should perform the BWE and the coded speech enhancement (CSE) at once. In this work, we propose to utilize two streaming SEANets in parallel, which are dedicated to the narrowband CSE and the generation of the upper band speech signal, respectively. Experimental results showed that the proposed model outperformed a bigger streaming SEANet trained to carry out both tasks in terms of the PESQ scores and the MUSHRA test.