Restoring clipped speech signal based on spectral transformation of each frequency band

Abstract

In recent years, high-quality speech recording is requested for comfortably using a communication system. However, a clipping distortion caused by input exceeding the maximum range of amplifier is one of the problems with a sound quality degradation. Although linear prediction method has been conventionally proposed for restoring a clipped speech signal, it has a problem that the frequently clipped speech signal degrades the restoration performance by increasing the prediction errors. In this paper, we propose a method for restoring a clipped speech signal based on a spectral transformation of each frequency band. In this method, the spectral envelope of target speech signal in each frame is approximated to the spectral envelope of original speech signal to remove the influence of a clipping distortion. In particular, the spectral envelope in higher frequency domain including a static characteristic of the speaker is replaced with the spectral envelope of the unclipped speech signal prepared in advance. Then, the spectral envelope in lower frequency domain including a characteristic of phoneme is approximated with Gaussian Mixture Models. We carried out an evaluation experiment for sound quality of speech signal processed by the proposed method. As a result, we confirmed the effectiveness of the proposed method.