TY  - JOUR
T1  - An Audio Declipping Method Based on Deep Neural Networks
AU  - Choi, Seung Un 
AU  - Choi, Seung Ho 
JO  - The Journal of Korean Institute of Communications and Information Sciences
PY  - 2022
DA  - 2022/1/15
DO  - 10.7840/kics.2022.47.9.1306
KW  - Audio declipping
KW  - Detection
KW  - deep neural network
KW  - Speech communication
KW  - Broadcasting audio
AB  - This paper is about declipping that restores the original sound from a clipped audio signal, and for this purpose, we propose a new method based on a deep neural network. This technique first detects clipping frames based on the number of clipped audio samples. Then, the network is trained using the magnitude spectra of the clipping frame and the original sound frame as input and output of the deep neural network. Through the experiment comparing the RMSE and LSD between the original sound and the reconstructed signal in the speech database, the proposed method showed that the performance was improved compared to the existing method.