语音增强Paper & Code

语音增强的模型代码

模型代码

• SEGAN
  Pascual S, Bonafonte A, Serrà J. SEGAN: Speech Enhancement Generative Adversarial Network[J]. Proc. Interspeech 2017, 2017: 3642-3646.
  代码链接：
  • tensorflow版本
  • pytorch版本
  • example of SEGAN
• Huang14Deep&Huang15Joint
  Huang P S, Kim M, Hasegawa-Johnson M, et al. Deep learning for monaural speech separation[C]//2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014: 1562-1566.
  代码链接：
  • 代码&数据集&paper
• Venkataramani18End
  Venkataramani S, Casebeer J, Smaragdis P. End-to-end source separation with adaptive front-ends[C]//2018 52nd Asilomar Conference on Signals, Systems, and Computers. IEEE, 2018: 684-688.
  代码链接：
  • github
  • 作者主页
• WangDeLiang团队
  • 主页
  • 论文与代码
  • DNN_toolbox：该toolbox可以获得WangDeLiang综述中的Training Target的matlab代码和data，见Wang17Supervised中的Figure2
• 各种传统方法的matlab代码(压缩包)
  • 下载链接
• RefineNet论文以及代码
  Lin G, Milan A, Shen C, et al. Refinenet: Multi-path refinement networks for high-resolution semantic segmentation[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 1925-1934.
  代码链接：
  • 各种类型的refineNet的github代码
• Park17Fully
  Park S R, Lee J W. A Fully Convolutional Neural Network for Speech Enhancement[J]. Proc. Interspeech 2017, 2017: 1993-1997.
  代码链接：
  • github地址
• Zheng19Phase-Aware（TASLP2019）
  Zheng N, Zhang X L. Phase-Aware Speech Enhancement Based on Deep Neural Networks[J]. IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2019, 27(1): 63-76.
  • 论文地址
  • github代码
• U-Net
  • 链接
  • pytorchUNet
  • pytorch resnet-Unet
• WAVE-U-NET
  • github代码
• Singing-U-Net
  • github代码
• Venkataramani的神经网络替代卷积音频模型用于源分离github
• deep complex network
• Speech enhancement GitHub检索
• Speech separation GitHub检索
• Topic: speech-separation · GitHub
• Topic: speech-enhancement · GitHub
• Topic: speech-denoising · GitHub
• Luo18TasNet论文及代码
  TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation
  • arXiv论文
  • Github代码
  • 主页
• Hershey16Deep
  Hershey J R, Chen Z, Le Roux J, et al. Deep clustering: Discriminative embeddings for segmentation and separation[C]//2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2016: 31-35.
  • Github:zhr1201/deep-clustering
  • arXiv
• DANet LuoYi 独立说话人分离
  • 主页
  • github

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blog

• WJ的blog
• Deep Learning Travels:包含一些语音分离/增强的内容
• Pelhans’s blog

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作者主页

• Jitong Chen的个人主页
• Jitong Chen的博士论文下载
• 神经声学处理实验室

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语音增强领域的主流方法和最新的方法

神经网络

• 7大类深度CNN架构创新综述