.. nnAudio documentation master file, created by sphinx-quickstart on Tue Dec 3 10:57:48 2019. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. nnAudio 0.2.0 =================================== Welcome to nnAudio 0.2.0. This new version changes the syntax of the spectrogram layers creation, such that ``stft_layer.to(device)`` can be used. This new version is more stable than the previous version since it is more compatible with other torch modules. nnAudio is an audio processing toolbox using PyTorch convolutional neural network as its backend. By doing so, spectrograms can be generated from audio on-the-fly during neural network training and the Fourier kernels (e.g. or CQT kernels) can be trained. `Kapre `__ has a similar concept in which they also use 1D convolutional neural network to extract spectrograms based on `Keras `__. Other GPU audio processing tools are `torchaudio `__ and `tf.signal `__. But they are not using the neural network approach, and hence the Fourier basis can not be trained. As of PyTorch 1.6.0, torchaudio is still very difficult to install under the Windows environment due to ``sox``. nnAudio is a more compatible audio processing tool across different operating systems since it relies mostly on PyTorch convolutional neural network. The name of nnAudio comes from ``torch.nn``. The implementation details for **nnAudio** have also been published in IEEE Access, people who are interested can read the `paper `__. The source code for **nnAudio** can be found in `GitHub `__. .. toctree:: :maxdepth: 1 :caption: Getting Started intro .. toctree:: :maxdepth: 1 :caption: API Documentation nnAudio .. toctree:: :maxdepth: 1 :caption: Tutorials examples .. toctree:: :maxdepth: 1 :caption: Citation citing Indices and tables ------------------ * :ref:`genindex` * :ref:`modindex`