Abstract
Clipping is a common problem in audio processing. Clipping distortion can be solved by the recently proposed consistent Dictionary Learning (cDL), but the performance of restoration will decrease when the clipping degree is large. To improve the performance of cDL, a method based on adaptive threshold is proposed. In this method, the clipping degree is estimated automatically, and the factor of the clipping degree is adjusted according to the degree of clipping. Experiments show the superior performance of the proposed algorithm with respect to cDL on audio signal restoration.
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Acknowledgements
Thanks are due to Mr. Zou for assistance with the experiments and to Mr. Sun for valuable discussion. This paper is supported by The National Natural Science Foundation of China (61471394) and The National Natural Foundation of Jiangsu Province for Excellent Young Scholars (BK20180080).
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Wu, P., Zou, X., Sun, M., Li, L., Zhang, X. (2019). Adaptive Consistent Dictionary Learning for Audio Declipping. In: Li, W., Li, S., Shao, X., Li, Z. (eds) Proceedings of the 6th Conference on Sound and Music Technology (CSMT). Lecture Notes in Electrical Engineering, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-13-8707-4_7
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DOI: https://doi.org/10.1007/978-981-13-8707-4_7
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