audio-data-pytorch and audio-encoders-pytorch
These are ecosystem siblings where the datasets and transforms tool provides training data and preprocessing for the autoencoders tool to consume during model training and inference.
About audio-data-pytorch
archinetai/audio-data-pytorch
A collection of useful audio datasets and transforms for PyTorch.
This tool helps machine learning engineers and researchers efficiently manage and preprocess various types of audio data for training machine learning models. It takes raw audio files from local folders, web datasets, or online sources like YouTube, and outputs pre-processed audio waveforms and associated metadata ready for model training. It's designed for anyone building speech recognition, audio classification, or other audio-centric AI applications.
About audio-encoders-pytorch
archinetai/audio-encoders-pytorch
A collection of audio autoencoders, in PyTorch.
This project provides pre-built neural network components designed to compress and reconstruct audio signals. It takes raw audio data as input and produces either a compressed representation or a reconstructed audio output. This is useful for audio developers and researchers working on advanced audio processing tasks like efficient storage, bandwidth reduction, or generating new audio.
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