A Digital Modeling Technique for Distortion Effect Based on a Machine Learning Approach.
Asia-Pacific Signal and Information Processing Association Annual Summit and Conference(2018)
摘要
This paper describes an experimental result of modeling stomp boxes of the distortion effect based on a machine learning approach. Our proposed technique models the distortion stomp boxes as a neural network consisting of CNN and LSTM. In this approach, CNN is employed for modeling the linear component that appears in the pre and post filters of the stomp boxes. On the other hand, LSTM is employed for modeling the nonlinear component that appears in the distortion process of the stomp boxes. All the parameters are estimated through the training process using the input and output signals of the distortion stomp boxes. The experimental result indicates that the proposed technique may have a certain potential to replicate the distortion stomp boxes appropriately by using the well-trained neural network.
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关键词
machine learning approach,distortion stomp boxes,neural network,distortion process,digital modeling technique,distortion effect,CNN,LSTM,linear component,nonlinear component,training process,output signals,input signals
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