SampleRNN_ICLR2017
Visit ToolsampleRNN_ICLR2017 is an open-source AI tool for unconditional end-to-end neural audio generation. It provides code and models for generating audio samples, including music.
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sampleRNN_ICLR2017 is an open-source AI tool for unconditional end-to-end neural audio generation. It provides code and models for generating audio samples, including music.
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sampleRNN_ICLR2017 is an open-source implementation of SampleRNN, a neural audio generation model designed for unconditional end-to-end audio synthesis. The project provides code and models for both two-tier and three-tier SampleRNN architectures, allowing users to generate audio samples, including music. It was extensively tested with Python 2.7.12, Numpy 1.11.1, Theano 0.8.2 (or 0.9 for WaveNet re-implementation), and Lasagne 0.2.dev1. The tool includes scripts for preprocessing and building music datasets, such as one created from Beethovenβs piano sonatas. It supports various parameters for training models, including frame size, embedding size, RNN type (LSTM/GRU), and quantization levels, making it suitable for AI research and development in audio synthesis.
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