Sound Texture Generative Model Guided by a Lossless Mel-Frequency Convolutional Neural Network
暂无分享,去创建一个
Weiwei Liu | Yuewei Dai | Guangjie Liu | Jiangtao Zhai | Xiaopeng Ji | Weiwei Liu | Yue-wei Dai | Xiaopeng Ji | Jiangtao Zhai | Yuewei Dai | Guangjie Liu
[1] Alexei A. Efros,et al. Context Encoders: Feature Learning by Inpainting , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Hermann Ney,et al. Computing Mel-frequency cepstral coefficients on the power spectrum , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).
[3] Rob Fergus,et al. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.
[4] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[5] Sung Yong Shin,et al. On pixel-based texture synthesis by non-parametric sampling , 2006, Comput. Graph..
[6] Karol J. Piczak. Environmental sound classification with convolutional neural networks , 2015, 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP).
[7] Eero P. Simoncelli,et al. Article Sound Texture Perception via Statistics of the Auditory Periphery: Evidence from Sound Synthesis , 2022 .
[8] Yang Lu,et al. Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching , 2018, AAAI.
[9] Tian Han,et al. Alternating Back-Propagation for Generator Network , 2016, AAAI.
[10] Thomas Brox,et al. Generating Images with Perceptual Similarity Metrics based on Deep Networks , 2016, NIPS.
[11] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[12] Dorothy T. Thayer,et al. EM algorithms for ML factor analysis , 1982 .
[13] Daan Wierstra,et al. Stochastic Backpropagation and Approximate Inference in Deep Generative Models , 2014, ICML.
[14] Wei Dai,et al. Very deep convolutional neural networks for raw waveforms , 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[15] Tatsuya Harada,et al. Learning environmental sounds with end-to-end convolutional neural network , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[16] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[17] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[18] Radford M. Neal. MCMC Using Hamiltonian Dynamics , 2011, 1206.1901.
[19] Alexei A. Efros,et al. Texture synthesis by non-parametric sampling , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[20] Tuomas Virtanen,et al. Filterbank learning for deep neural network based polyphonic sound event detection , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).
[21] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[22] Daniel P. W. Ellis,et al. Sound texture modelling with linear prediction in both time and frequency domains , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[23] Arun Kumar Sangaiah,et al. Automatic Generation of News Comments Based on Gated Attention Neural Networks , 2018, IEEE Access.
[24] Thomas Brox,et al. Learning to generate chairs with convolutional neural networks , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Karol Gregor,et al. Neural Variational Inference and Learning in Belief Networks , 2014, ICML.
[26] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Justin Salamon,et al. Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification , 2016, IEEE Signal Processing Letters.
[28] Eero P. Simoncelli,et al. Sound texture synthesis via filter statistics , 2009, 2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.