论文标题
两个步骤的向后兼容的成额外语音增强系统
A two-step backward compatible fullband speech enhancement system
论文作者
论文摘要
基于深度学习的语音增强方法超过了传统方法。尽管这些新方法中有许多正在以宽带（16kHz）的样本速率进行操作，但本文提出了一种新的成高器（48kHz）语音增强系统。与现有的成熟功能使用单个网络结构来训练成型者语音增强功能的现有成本系统相比，提出的系统是两步系统，可确保良好的成型成式语音增强质量，同时向后兼容现有的宽带系统。
Speech enhancement methods based on deep learning have surpassed traditional methods. While many of these new approaches are operating on the wideband (16kHz) sample rate, a new fullband (48kHz) speech enhancement system is proposed in this paper. Compared to the existing fullband systems that utilizes perceptually motivated features to train the fullband speech enhancement using a single network structure, the proposed system is a two-step system ensuring good fullband speech enhancement quality while backward compatible to the existing wideband systems.
