To overcome the limitation and obtain more appropriate control filters, a generative fixed-filter active noise control (GFANC) approach is proposed in this paper. Specifically, various control filters can be generated by using different hard weights to combine pre-trained sub control filters. The hard weights are automatically obtained via a one-dimensional convolutional neural network given the incoming noise.