Shypd.aiThe largest open index of AI toolstorch-audiomentations is a PyTorch library for fast audio data augmentation, supporting both CPU and GPU processing. It integrates seamlessly into PyTorch neural network models, handling batches of multichannel audio.
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torch-audiomentations is a PyTorch library designed for efficient audio data augmentation, crucial for deep learning applications. It prioritizes speed by supporting both CPU and GPU (CUDA) processing, making it suitable for large-scale model training. The library handles batches of multichannel or mono audio and its transforms extend `nn.Module`, allowing direct integration into PyTorch neural network models. Most transforms are differentiable, offering flexibility for advanced use cases. It features three modes—per_batch, per_example, and per_channel—for applying augmentations, along with a permissive MIT license and cross-platform compatibility. The library includes a variety of waveform transforms such as Gain, PolarityInversion, AddBackgroundNoise, PitchShift, and various filters, aiming for high test coverage and continuous development.
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